Validation of high-throughput sequencing-based test system for detection of microsatellite instability in colorectal cancer samples ; Валидация тест-системы на основе высокопроизводительного секвенирования для детектирования микросателлитной нестабильности в образцах колоректального рака

Authors: Lebedeva A.A., Taraskina A.N., Kavun A.I., Belova E.V., Grigor'eva T.V., Kuznetsova O.A., Kravchuk D.A., Belyaeva L.D., Nikulin V.E., Khomenko E.D., Mileyko V.A., Tryakin A.A., Fedyanin M.Y., Ivanov M.V.

Contributors: The research was supported by a grant from the Russian Science Foundation (grant No. 22-75-10154)., Исследование выполнено при поддержке гранта Российского научного фонда (грант № 22-75-10154).

Source: Advances in Molecular Oncology; Vol 12, No 1 (2025); 41-52 ; Успехи молекулярной онкологии; Vol 12, No 1 (2025); 41-52 ; 2413-3787 ; 2313-805X

Subject Terms: high-throughput sequencing, next generation sequencing, microsatellite, высокопроизводительное секвенирование, секвенирование нового поколения, микросателлитная нестабильность

File Description: application/pdf

Relation: https://umo.abvpress.ru/jour/article/view/756/380; https://umo.abvpress.ru/jour/article/view/756

Availability: https://umo.abvpress.ru/jour/article/view/756
https://doi.org/10.17650/2313-805X-2025-12-1-41-52

ВАРИАНТЫ В ГЕНАХ ДЛИННЫХ НЕКОДИРУЮЩИХ РНК ПРИ ПАРАГАНГЛИОМАХ ГОЛОВЫ И ШЕИ

Source: Journal of Bioinformatics and Genomics, Vol 25, Iss 3 (2024)

Subject Terms: long non-coding rnas, genetic variants, head and neck paraganglioma, high-throughput sequencing, QH426-470, высокопроизводительное секвенирование, параганглиома головы и шеи, длинные некодирующие рнк, long non-coding RNAs, длинные некодирующие РНК, генетические варианты, Genetics, экзом, exome

Access URL: https://doaj.org/article/3ab73394b29840bd8da7280c3cc7f6a2

Comparative analysis of the profile of circulating microRNAs in the blood plasma of patients with gliomas ; Сравнительный анализ профиля циркулирующих микроРНК в плазме крови пациентов с глиальными опухолями мозга

Authors: D. Yu. Gvaldin, N. A. Petrusenko, E. E. Rostorguev, S. N. Dimitriadi, S. E. Kavitskiy, N. N. Timoshkina, Д. Ю. Гвалдин, Н. А. Петрусенко, Э. Е. Росторгуев, С. Н. Димитриади, С. Э. Кавицкий, Н. Н. Тимошкина

Contributors: the financial support of this work was provided within the framework of the state task "Development of a minimally invasive diagnostic panel for brain tumors based on circulating microRNAs in blood plasma"., финансирование данной работы проводилось в рамках госзадания «Разработка малоинвазивной диагностической панели опухолей головного мозга на основе циркулирующих микроРНК в плазме крови».

Source: Research and Practical Medicine Journal; Том 11, № 2 (2024); 36-45 ; Research'n Practical Medicine Journal; Том 11, № 2 (2024); 36-45 ; 2410-1893 ; 10.17709/2410-1893-2024-11-2

Subject Terms: циркулирующие биомаркеры, gliomas, meningiomas, high-output sequencing, circulating biomarkers, глиальные опухоли, менингиомы, высокопроизводительное секвенирование

File Description: application/pdf

Relation: https://www.rpmj.ru/rpmj/article/view/989/618; https://www.rpmj.ru/rpmj/article/view/989/627; Pellerino A, Caccese M, Padovan M, Cerretti G, Lombardi G. Epidemiology, risk factors, and prognostic factors of gliomas. Clin Transl Imaging. 2022;10:467–475. https://doi.org/10.1007/s40336-022-00489-6; Mathew EN, Berry BC, Yang HW, Carroll RS, Johnson MD. Delivering Therapeutics to Glioblastoma: Overcoming Biological Constraints. Int J Mol Sci. 2022 Feb 2;23(3):1711. https://doi.org/10.3390/ijms23031711; Fisher JP, Adamson DC. Current FDA-Approved Therapies for High-Grade Malignant Gliomas. Biomedicines. 2021 Mar 22;9(3):324. https://doi.org/10.3390/biomedicines9030324; Кузнецова Н. С., Гурова С. В., Гончарова A. С., Заикина Е. В., Гусарева М. А., Зинькович М. С. Современные подходы к терапии глиобластомы. Южно-Российский онкологический журнал. 2023;4(1):52–64. https://doi.org/10.37748/2686-9039-2023-4-1-6 EDN: IICMMC; Gvaldin DYu, Pushkin AA, Timoshkina NN, Rostorguev EE, Nalgiev AM, Kit OI. Integratime analysis of mRNA and miRNA seprencing data for gliomas of various grades. Egyptian Journal of Medical Human Genetics. 2020;21:73 https://doi.org/10.1186/s43042-020-00119-8; Пушкин А. А., Тимошкина Н. Н., Гвалдин Д. Ю., Дженкова Е. А. Анализ данных высокопроизводительного секвенирования и микрочипов для идентификации ключевых сигнатур микрорибонуклеиновых кислот в глиобластоме. Research and Practical Medicine Journal (Исследования и практика в медицине). 2021;8(3):21–33. https://doi.org/10.17709/2410-1893-2021-8-3-2; Sati ISEE, Parhar I. MicroRNAs Regulate Cell Cycle and Cell Death Pathways in Glioblastoma. Int J Mol Sci. 2021 Dec 17;22(24):13550. https://doi.org/10.3390/ijms222413550; Mahinfar P, Mansoori B, Rostamzadeh D, Baradaran B, Cho WC, Mansoori B. The Role of microRNAs in Multidrug Resistance of Glioblastoma. Cancers (Basel). 2022 Jun 30;14(13):3217. https://doi.org/10.3390/cancers14133217; Ahmed SP, Castresana JS, Shahi MH. Role of Circular RNA in Brain Tumor Development. Cells. 2022 Jul 6;11(14):2130. https://doi.org/10.3390/cells11142130; Пушкин А. А., Гвалдин Д. Ю., Тимошкина Н. Н., Росторгуев Э. Е., Владимирова Л. Ю., Дженкова Е. А. Анализ данных высокопроизводительного секвенирования базы Gene Expression Omnibus для идентификации микрорибонуклеиновых кислот в плазме крови пациентов с глиобластомой. Research and Practical Medicine Journal (Исследования и практика в медицине). 2022;9(1):54–64. https://doi.org/10.17709/2410-1893-2022-9-1-5; Kit OI, Pushkin AA, Alliluyev IA, Timoshkina NN, Gvaldin DYu, Rostorguev EE, Kuznetsova NS. Differential expression of microRNAs targeting genes associated with the development of high-grade gliomas. Egyptian Journal of Medical Human Genetics. 2022;23(31). https://doi.org/10.1186/s43042-022-00245-5; Valihrach L, Androvic P, Kubista M. Circulating miRNA analysis for cancer diagnostics and therapy. Mol Aspects Med. 2020 Apr;72:100825. https://doi.org/10.1016/j.mam.2019.10.002; Пушкин А. А., Кит О. И., Росторгуев Э. Е., Новикова И. А., Дженкова Е. А., Тимошкина Н. Н., и др. Способ малоинвазивной диагностики менингиом и опухолей глиального ряда с уточнением степени злокачественности. Патент на изобретение 2788814 C1, 24.01.2023.; Müller Bark J, Kulasinghe A, Chua B, Day BW, Punyadeera C. Circulating biomarkers in patients with glioblastoma. Br J Cancer. 2020 Feb;122(3):295–305. https://doi.org/10.1038/s41416-019-0603-6; Yi Z, Qu C, Zeng Y, Liu Z. Liquid biopsy: early and accurate diagnosis of brain tumor. J Cancer Res Clin Oncol. 2022 Sep;148(9):2347– 2373. https://doi.org/10.1007/s00432-022-04011-3; Caputo V, Ciardiello F, Corte CMD, Martini G, Troiani T, Napolitano S. Diagnostic value of liquid biopsy in the era of precision medicine: 10 years of clinical evidence in cancer. Explor Target Antitumor Ther. 2023;4(1):102–138. https://doi.org/10.37349/etat.2023.00125; Licursi V, Conte F, Fiscon G, Paci P. MIENTURNET: an interactive web tool for microRNA-target enrichment and network-based analysis. BMC Bioinformatics. 2019 Nov 4;20(1):545. https://doi.org/10.1186/s12859-019-3105-x; Пушкин А. А., Гвалдин Д. Ю., Петрусенко Н. А., Росторгуев Э. Е., Кавицкий С. Э., Тимошкина Н. Н. Уровень опухолевых и внеклеточных микроРНК у пациентов с глиальными опухолями головного мозга. Современные проблемы науки и образования. 2023;5. https://doi.org/10.17513/spno.32954; Dong L, Li Y, Han C, Wang X, She L, Zhang H. miRNA microarray reveals specific expression in the peripheral blood of glioblastoma patients. Int J Oncol. 2014 Aug;45(2):746–756. https://doi.org/10.3892/ijo.2014.2459; Akers JC, Hua W, Li H, Ramakrishnan V, Yang Z, Quan K, et al. A cerebrospinal fluid microRNA signature as biomarker for glioblastoma. Oncotarget. 2017 Jun 1;8(40):68769–68779. https://doi.org/10.18632/oncotarget.18332; Lu S, Yu Z, Zhang X, Sui L. MiR-483 Targeted SOX3 to Suppress Glioma Cell Migration, Invasion and Promote Cell Apoptosis. Onco Targets Ther. 2020 Mar 9;13:2153–2161. https://doi.org/10.2147/ott.s240619; Buonfiglioli A, Efe IE, Guneykaya D, Ivanov A, Huang Y, Orlowski E, et al. let-7 MicroRNAs Regulate Microglial Function and Suppress Glioma Growth through Toll-Like Receptor 7. Cell Rep. 2019 Dec 10;29(11):3460–3471.e7. https://doi.org/10.1016/j.celrep.2019.11.029; Duan ML, Du XM. The Crosstalk between MicroRNA-196a and Annexin-A1: A Potential Mechanism for Oral Squamous Cell Carcinoma Progression. Indian J Pharm Sci. 2022;84(5):144–151 https://doi.org/10.36468/pharmaceutical-sciences.spl.581; Gao F, Cui Y, Jiang H, Sui D, Wang Y, Jiang Z, et al. Circulating tumor cell is a common property of brain glioma and promotes the monitoring system. Oncotarget. 2016 Nov 1;7(44):71330–71340. https://doi.org/10.18632/oncotarget.11114; https://www.rpmj.ru/rpmj/article/view/989

Availability: https://www.rpmj.ru/rpmj/article/view/989
https://doi.org/10.17709/2410-1893-2024-11-2-3

Validation of PMS2 germline variants in patients with hereditary cancer syndromes ; Особенности валидации герминальных вариантов в гене PMS2 у пациентов с наследственными опухолевыми синдромами

Authors: M. A. Revkova, A. A. Krinitsina, M. V. Nemtsova, M. V. Makarova, D. K Chernevskiy, O. V. Sagaydak, V. S. Mikhailov, P. V. Ulanova, A. S. Tsukanov, M. M. Byakhova, A. B. Semenova, V. N. Galkin, Ch. V. Babajanova, A. M. Danishevich, N. A. Bodunova, S. M. Gadzhieva, M. S. Belinikin, М. А. Ревкова, А. А. Криницина, М. В. Немцова, М. В. Макарова, Д. К. Черневский, О. В. Сагайдак, В. С. Михайлов, П. В. Уланова, А. С. Цуканов, М. М. Бяхова, А. Б. Семенова, В. Н. Галкин, Ч. В. Бабаджанова, А. М. Данишевич, Н. А. Бодунова, С. М. Гаджиева, М. С. Белиникин

Contributors: This research was supported by the Moscow Healthcare Department., Исследование проведено за счет средств гранта Департамента здравоохранения г. Москвы.

Source: Medical Genetics; Том 23, № 2 (2024); 34-45 ; Медицинская генетика; Том 23, № 2 (2024); 34-45 ; 2073-7998

Subject Terms: наследственные опухолевые синдромы, next-generation sequencing, Sanger sequencing, hereditary cancer syndromes, высокопроизводительное секвенирование, секвенирование по Сэнгеру

File Description: application/pdf

Relation: https://www.medgen-journal.ru/jour/article/view/2420/1772; Vanin E.F. Processed pseudogenes: characteristics and evolution. Annu Rev Genet. 1985;19:253-72. doi:10.1146/annurev.ge.19.120185.001345.; Claes K.B.M., Rosseel T., De Leeneer K. Dealing with Pseudogenes in Molecular Diagnostics in the Next Generation Sequencing Era. Methods Mol Biol. 2021;2324:363-381. doi:10.1007/978-1-0716-1503-4_22.; van der Klift H.M., Tops C.M., Bik E.C., et al. Quantification of sequence exchange events between PMS2 and PMS2CL provides a basis for improved mutation scanning of Lynch syndrome patients. Hum Mutat. 2010 May;31(5):578-87. doi:10.1002/humu.21229.; Clendenning M., Hampel H., LaJeunesse J., et al. Long-range PCR facilitates the identification of PMS2-specific mutations. Hum Mutat. 2006 May;27(5):490-5. doi:10.1002/humu.20318. Erratum in: Hum Mutat. 2006;27(11):1155.; Vaughn C.P., Robles J., Swensen J.J., et al. Clinical analysis of PMS2: mutation detection and avoidance of pseudogenes. Hum Mutat. 2010;31(5):588-93. doi:10.1002/humu.21230.; Рыжкова О.П., Кардымон О.Л., Прохорчук Е.Б., и др. Руководство по интерпретации данных последовательности ДНК человека, полученных методами массового параллельного секвенирования (MPS) (редакция 2018, версия 2). Медицинская генетика. 2019;18(2):3-23. https://doi.org/10.25557/2073-7998.2019.02.3-23; Hereditary Cancer Syndromes and Risk Assessment: ACOG COMMITTEE OPINION, Number 793. Obstet Gynecol. 2019;134(6):e143-e149. doi:10.1097/AOG.0000000000003562.; Nicolaides N.C., Papadopoulos N., Liu B., et al. Mutations of two PMS homologues in hereditary nonpolyposis colon cancer. Nature. 1994;371(6492):75-80. doi:10.1038/371075a0.; Senter L., Clendenning M., Sotamaa K., et al. The clinical phenotype of Lynch syndrome due to germline PMS2 mutations. Gastroenterology. 2008;135(2):419-28. doi:10.1053/j.gastro.2008.04.026.; Ten Broeke S.W., van der Klift H.M., Tops C.M.J., et al. Cancer Risks for PMS2-Associated Lynch Syndrome. J Clin Oncol. 2018;36(29):2961-2968. doi:10.1200/JCO.2018.78.4777. Erratum in: J Clin Oncol. 2019 Mar 20;37(9):761.; Cannavo E., Marra G., Sabates-Bellver J., et al. Expression of the MutL homologue hMLH3 in human cells and its role in DNA mismatch repair. Cancer Res. 2005;65(23):10759-66. doi:10.1158/0008-5472.CAN-05-2528.; Korhonen M.K., Raevaara T.E., Lohi H., Nyström M. Conditional nuclear localization of hMLH3 suggests a minor activity in mismatch repair and supports its role as a low-risk gene in HNPCC. Oncol Rep. 2007;17(2):351-4.; ten Broeke S.W., Brohet R.M., Tops C.M., et al. Lynch syndrome caused by germline PMS2 mutations: delineating the cancer risk. J Clin Oncol. 2015;33(4):319-25. doi:10.1200/JCO.2014.57.8088.; Шелыгин Ю.А., Ачкасов С.И., Семёнов Д.А., и др. Генетические и фенотипические характеристики 60 российских семей с синдромом Линча. Колопроктология. 2021;20(3):35–42. http://dx.doi.org/10.33878/2073-7556-2021-20-3-35-42; Kasela M., Nyström M., Kansikas M. PMS2 expression decrease causes severe problems in mismatch repair. Hum Mutat. 2019;40(7):904-907. doi:10.1002/humu.23756.; Hendriks Y.M., Jagmohan-Changur S., van der Klift H.M., et al. Heterozygous mutations in PMS2 cause hereditary nonpolyposis colorectal carcinoma (Lynch syndrome). Gastroenterology. 2006;130(2):312-22. doi:10.1053/j.gastro.2005.10.052.; Clendenning M., Hampel H., LaJeunesse J., et al. Long-range PCR facilitates the identification of PMS2-specific mutations. Hum Mutat. 2006;27(5):490-5. doi:10.1002/humu.20318. Erratum in: Hum Mutat. 2006;27(11):1155.; Li J., Dai H., Feng Y., et al. A Comprehensive Strategy for Accurate Mutation Detection of the Highly Homologous PMS2. J Mol Diagn. 2015;17(5):545-53. doi:10.1016/j.jmoldx.2015.04.001.; Nicolaides N.C., Kinzler K.W., Vogelstein B. Analysis of the 5’ region of PMS2 reveals heterogeneous transcripts and a novel overlapping gene. Genomics. 1995;29(2):329-34. doi:10.1006/geno.1995.9997.; Hayward B.E., De Vos M., Valleley E.M., et al. Extensive gene conversion at the PMS2 DNA mismatch repair locus. Hum Mutat. 2007;28(5):424-30. doi:10.1002/humu.20457. PMID: 17253626.; Auclair J., Leroux D., Desseigne F., et al. Novel biallelic mutations in MSH6 and PMS2 genes: gene conversion as a likely cause of PMS2 gene inactivation. Hum Mutat. 2007;28(11):1084-90. doi:10.1002/humu.20569.; Ganster C., Wernstedt A., Kehrer-Sawatzki H., et al. Functional PMS2 hybrid alleles containing a pseudogene-specific missense variant trace back to a single ancient intrachromosomal recombination event. Hum Mutat. 2010;31(5):552-60. doi:10.1002/humu.21223.; Семенова А. Б., Бяхова М. М., Галкин В. Н., и др. Возможности молекулярно-генетических методов для эффективного выявления наследственных форм онкологических заболеваний среди лиц с повышенными рисками их развития. Здоровье мегаполиса. 2023; 4(2):30-40. doi:10.47619/2713-2617.zm.2023.v.4i2;30-40.

Availability: https://www.medgen-journal.ru/jour/article/view/2420
https://doi.org/10.25557/2073-7998.2024.02.34-45

Sequencing and analysis of the complete genome of the Russian cherry virus A isolate ; Секвенирование и анализ полного генома российского изолята вируса А черешни (cherry virus A)

Authors: E. V. Motsar, A. A. Sheveleva, F. S. Sharko, I. V. Mitrofanova, S. N. Chirkov, Е. В. Моцарь, А. А. Шевелева, Ф. С. Шарко, И. В. Митрофанова, С. Н. Чирков

Contributors: The research was funded by Russian Science Foundation, project number 23-16-00032., Работа выполнена при финансовой поддержке Российского научного фонда (грант № 23-16-00032).

Source: Vestnik Moskovskogo universiteta. Seriya 16. Biologiya; Том 79, № 3 (2024); 221-226 ; Вестник Московского университета. Серия 16. Биология; Том 79, № 3 (2024); 221-226 ; 0137-0952

Subject Terms: филогенетический анализ, germplasm collections, plant viruses, cherry virus A, high-throughput sequencing, phylogenetic analysis, генофондовые коллекции, фитовирусы, вирус А черешни, высокопроизводительное секвенирование

File Description: application/pdf

Relation: https://vestnik-bio-msu.elpub.ru/jour/article/view/1410/694; Hadidi A., Barba M. Economic impact of pome and stone fruit viruses and viroids. Virus and virus-like diseases of pome and stone fruits. Eds. A. Hadidi, M. Barba, T. Candresse, W. Jelkmann W. St. Paul: APS Press; 2011. 428 pp.; Maliogka V., Minafra A., Saldarelli P., RuizGarcía A., Glasa M., Katis N., Olmos A. Recent advances on detection and characterization of fruit tree viruses using high-throughput sequencing technologies. Viruses. 2018;10(8):436.; Rubio M., Martinez-Gomez P., Marais A., Sanches-Navarro J.A., Pallas V., Candresse T. Recent advances and prospect in Prunus virology. Ann. Appl. Biol. 2017;171(2):125−138.; Rott M., Xiang Y., Boyes I., Belton M., Saeed H., Kesanakurti P., Hayes S., Lawrence T., Birch C., Bhagwat B., Rast H. Application of next generation sequencing for diagnostic testing of tree fruit viruses and viroids. Plant Dis. 2017;101(8):1489−1499.; Приходько Ю.Н., Живаева Т.С., Шнейдер Ю.А., Кондратьев М.О. Видовой состав и распространенность вирусов в насаждениях косточковых культур Европейской части Российской Федерации. Бюл. ГНБС. 2024;150:63−68.; Jelkmann W. Cherry virus A: cDNA cloning of dsRNA, nucleotide sequence analysis and serology reveal a new plant capillovirus in sweet cherry. J. Gen. Virol. 1995;76(8):2015−2024.; Kesanakurti P., Belton M., Saeed H., Rast H., Boyes I., Rott M. Comparative analysis of cherry virus A genome sequences assembled from deep sequencing data. Arch. Virol. 2017;162(9):2821–2828.; Marais A., Candresse T., Svanella-Dumas L., Jelkmann W. Cherry virus A. Virus and virus-like diseases of pome and stone fruits. Eds. A. Hadidi, M. Barba, T. Candresse and W. Jelkmann. St. Paul: APS Press; 2011. 428 pp.; James D., Jelkmann W. Detection of cherry virus A in Canada and Germany. Acta Hortic. 1998;472:299–303.; Marais A., Svanella-Dumas L., Barone M., Gentit P., Faure C., Charlot G., Ragozzino A., Candresse T. Development of a polyvalent RT-PCR assay covering the genetic diversity of Cherry capillovirus A. Plant Pathol. 2012;61(1):195−204.; Chirkov S., Sheveleva A., Tsygankova S., Slobodova N., Sharko F., Petrova K., Mitrofanova I. First report and complete genome characterization of cherry virus A and little cherry virus 1 from Russia. Plants. 2023;12(18):3295.; Gambino G., Perrone I., Gribaudo I. A rapid and effective method for RNA extraction from different tissues of grapevine and other woody plants. Phytochem. Anal. 2008;19(6):520–525.; Nurk S., Meleshko D., Korobeynikov A., Pevzner P.A. metaSPAdes: A new versatile metagenomic assembler. Genome Res. 2017;27(5):824–834.; Langmead B., Salzberg S. Fast gapped-read alignment with Bowtie 2. Nat. Methods. 2012;9(4):357–359.; Kumar S., Stecher G., Li M., Knyaz C., Tamura K. MEGA X: Molecular evolutionary genetics analysis across computing platforms. Mol. Biol. Evol. 2018;35(6):1547–1549.; Noorani M.S., Khan A.J., Khursheed S. Molecular characterization of cherry virus A and prunus necrotic ringspot virus and their variability based on nucleotide polymorphism. Arch. Phytopathol. Plant Protect. 2022;55(4):387–404.; Gao R., Xu Y., Candresse T., He Z., Li S., Ma Y., Lu M. Further insight into genetic variation and haplotype diversity of Cherry virus A from China. PloS One. 2017;12(10):e0186273.; Noorani M.S., Awasthi P., Singh R.M., Ram R., Sharma M.P., Singh S.R., Ahmed N., Hallan V., Zaid A.A. Complete nucleotide sequence of cherry virus A (CVA) infecting sweet cherry in India. Arch. Virol. 2010;155(12):2079–2082.; Kinoti W.M., Nancarrow N., Dann A., Rodoni B.C., Constable F.E. Updating the quarantine status of Prunus infecting viruses in Australia. Viruses. 2020;12(2):246.; Cao X., Tian L., Yuan X., Andika I.B. Development of a multiplex RT-PCR and the occurrence characteristics of viral diseases in sweet cherries in the Shandong province, China. Physiol. Mol. Plant Pathol. 2022;121:101881.

Availability: https://vestnik-bio-msu.elpub.ru/jour/article/view/1410
https://doi.org/10.55959/MSU0137-0952-16-79-3-6

A study of macroinvertebrate communities in Bolshiye Koty Bay of Lake Baikal using DNA metabarcoding ; Исследование сообществ макробеспозвоночных животных в бухте Большие Коты озера Байкал с использованием ДНК метабаркодинга

Authors: L. S. Kravtsova, T. E. Peretolchina, T. I. Triboy, I. A. Nebesnykh, A. E. Tupikin, M. R. Kabilov, Л. С. Кравцова, Т. Е. Перетолчина, Т. И. Трибой, И. А. Небесных, А. Е. Тупикин, М. Р. Кабилов

Contributors: The work was supported by the project of the Russian Foundation for Basic Research No. 19-05-00398_a. Collection and analysis of samples was partially carried out within the state-funded project conducted by LIN SB RAS No. 121032300196-8, bioinformatics analysis was partially supported by the state-funded project conducted by LIN SB RAS No. 121031300042-1

Source: Vavilov Journal of Genetics and Breeding; Том 27, № 6 (2023); 694-702 ; Вавиловский журнал генетики и селекции; Том 27, № 6 (2023); 694-702 ; 2500-3259 ; 10.18699/VJGB-23-65

Subject Terms: Байкал, diversity, DNA metabarcoding, COI, high-throughput sequencing technologies, Lake Baikal, разнообразие, ДНК метабаркодинг, СОI, высокопроизводительное секвенирование

File Description: application/pdf

Relation: https://vavilov.elpub.ru/jour/article/view/3941/1755; Arbačiauskas K., Semenchenko V., Grabovski M., Leuven R., Paunović M., Son M., Csanyi B., Gumuliauskaitè S., Konopacka A., Nehring S., van der Velde G., Vezhnovetz V., Panov V. Assessment of biocontamination of benthic macroinvertebrate communities in European inland waterways. Aquat. Invasions. 2008;3(2):211­230. DOI:10.3391/ai.2008.3.2.12.; Aylagas E., Borja A., Rodríguez­Ezpeleta N. Environmental status assessment using DNA metabarcoding: towards a genetics based marine biotic index (gAMBI). PLoS One. 2014;9(3):e90529. DOI:10.1371/journal.pone.0090529.; Bailey R.C., Norris R.H., Reynoldson T.B. Taxonomic resolution of benthic macroinvertebrate communities in bioassessments. J. North Am. Benthol. Soc. 2001;20(2):280­286. DOI:10.2307/1468322.; Begon M., Harper J., Townsend K. Ecology: From Individuals to Ecosystems. Malden, MA: Blackwell Publishing, 1986. (Russ. ed.: Begon M., Harper J., Taunsend K. Ekologiya. Moscow: Mir Publ., 1989); Bonada N., Dolédec S., Statzner B. Taxonomic and biological trait differences of stream macroinvertebrate communities between mediterranean and temperate regions: implications for future climatic scenarios. Glob. Chang. Biol. 2007;13(8):1658­1671. DOI:10.1111/j.1365­2486.2007.01375.x.; Brauns M., Garcia X.­F., Pusch M.T., Walz N. Eulittoral macroinvertebrate communities of lowland lakes: discrimination among trophic states. Freshw. Biol. 2007;52(6):1022­1032. DOI:10.1111/j.13652427.2007.01.; Brotskaya V.A., Zenkevich L.A. Quantitative accounting of the benthic fauna of the Barents Sea. Proceedings of Russian Federal Research Institute of Fisheries and Oceanography. 1939;4:5­98. (in Russian); Burgmer T., Hillebrand H., Pfenninger M. Effects of climate­driven temperature changes on the diversity of freshwater macroinvertebrates. Oecologia. 2007;151(1):93­103. DOI:10.1007/s00442­0060542­9.; Derycke S., Vanaverbeke J., Rigaux A., Backeljau T., Moens T. Exploring the use of cytochrome oxidase c subunit 1 (COI) for DNA barcoding of free­living marine nematodes. PLoS One. 2010;5(10): e13716. DOI:10.1371/journal.pone.0013716.; Doyle J.J., Dickson E.E. Preservation of plant samples for DNA restriction endonuclease analysis. Taxon. 1987;36(4):715­722. DOI:10.2307/1221122.; Edgar R.C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics. 2010;26(19):2460­2461. DOI:10.1093/bioinformatics/btq461.; Edgar R.C. UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nat. Methods. 2013;10(10):996­998. DOI:10.1038/nmeth.2604.; Edgar R.C. SINTAX, a Simple Non­Bayesian Taxonomy Classifier for 16S and ITS sequences. bioRxiv. 2016. DOI:10.1101/074161.; Elbrecht V., Leese F. Can DNA­based ecosystem assessments quantify species abundance? Testing primer bias and biomass – sequence relationships with an innovative metabarcoding protocol. PLoS One. 2015;10(7):e0130324. DOI:10.1371/journal.pone.0130324.; Elbrecht V., Vamos E.E., Meissner K., Aroviita J., Leese F. Assessing strengths and weaknesses of DNA metabarcoding­based macroinvertebrate identification for routine stream monitoring. Methods Ecol. Evol. 2017;8(10):1265­1275. DOI:10.1111/2041­210X.12789.; Folmer O., Hoeh W.R., Black M.B., Vrijenhoek R.C. Conserved primers for PCR amplification of mitochondrial DNA from different invertebrate phyla. Mol. Mar. Biol. Biotechnol. 1994;3(5):294­299.; Geller J., Meyer C., Parker M., Hawk H. Redesign of PCR primers for mitochondrial cytochrome c oxidase subunit I for marine invertebrates and application in all­taxa biotic surveys. Mol. Ecol. Resour. 2013;13(5):851­861. DOI:10.1111/1755­0998.12138.; Gleason J.E., Elbrecht V., Braukmann T.W.A., Hanner R.H., Cottenie K. Assessment of stream macroinvertebrate communities with eDNA is not congruent with tissue­based metabarcoding. Mol. Ecol. 2021;30(13):3239­3251. DOI:10.1111/mec.15597.; Haenel Q., Holovachov O., Jondelius U., Sundberg P., Bourlat S.J. NGSbased biodiversity and community structure analysis of meiofaunal eukaryotes in shell sand from Hållö island, Smögen, and soft mud from Gullmarn Fjord, Sweden. Biodivers. Data J. 2017;5:e12731. DOI:10.3897/BDJ.5.e12731.; Hajibabaei M., Shokralla S., Zhou X., Singer G.A.C., Baird D.J. Environmental barcoding: a next­generation sequencing approach for biomonitoring applications using river benthos. PLoS One. 2011; 6(4):e17497. DOI:10.1371/journal.pone.0017497.; Hampton S.E., McGowan S., Ozersky T., Virdis S.G.P., Vu T.T., Spanbauer T.L., Kraemer B.M., Swann G., Mackay A.W., Powers S.M., Meyer M.F., Labou S.G., O’Reilly C.M., DiCarlo M., Galloway A.W.E., Fritz S.C. Recent ecological change in ancient lakes. Limnol. Oceanogr. 2018;63(5):2277­2304. DOI:10.1002/lno.10938.; Hebert P.D.N., Cywinska A., Ball S.L., DeWaard J.R. Biological identifications through DNA barcodes. Proc. Biol. Sci. 2003;270(1512): 313­321. DOI:10.1098/rspb.2002.2218.; Hsieh T.C., Ma K.H., Chao A. iNEXT: an R package for rarefaction and extrapolation of species diversity (Hill numbers). Methods Ecol. Evol. 2016;7(12):1451­1456. DOI:10.1111/2041­210X.12613.; Konstantinov A.S. General Hydrobiology. Moscow, 1986. (in Russian) Kravtsova L.S., Karabanov E.B., Kamaltynov R.M., Mekhani kova I.V., Sitnikova T.Ya., Rozhkova N.A., Slugina Z.V., Izhboldina L.A., Weinberg I.V., Akinshina T.V., Krivonogov S.K., Shcherbakov D. Yu. Macrozoobenthos of subaqueous landscapes in the shoal of southern; Lake Baikal: 1. Local diversity of bottom populations and features of their spatial distribution. Zoologicheskiy Zhurnal = Zoological Journal. 2003;82(3):307­317. (in Russian); Kravtsova L.S., Kamaltynov R.M., Karabanov E.B., Mekhanikova I.V., Sitnikova T.Ya., Rozhkova N.F., Slugina Z.V., Izhboldina L.A., Weinberg I.V., Akinshina T.V., Sherbakov D.Yu. Macrozoobenthic communities of underwater landscapes in the shallow­water zone of southern Lake Baikal. Hydrobiol. 2004;522:193­205. DOI:10.1023/B:HYDR.0000029979.68265.3e.; Kravtsova L.S., Peretolchina T.E., Triboy T.I., Sherbakov D.Y. The evolutionary history of two species of Orthocladiinae (Diptera: Chironomidae) from Lake Baikal (Eastern Siberia). Aquat. Insects. 2014;36(3­4):171­185. DOI:10.1080/01650424.2015.1062111.; Kravtsova L.S., Peretolchina T.E., Triboy T.I., Nebesnykh I.A., Kupchinskiy A.B., Tupikin A.E., Kabilov M.R. The study of the diversity of hydrobionts from Listvennichny Bay of Lake Baikal by DNA metabarcoding. Russ. J. Genet. 2021;57(4):460­467. DOI:10.1134/s1022795421040050.; Kuntke F., de Jonge N., Hesselsøe M., Nielsen J.L. Stream water qua lity assessment by metabarcoding of invertebrates. Ecol. Indic. 2020; 111:105982. DOI:10.1016/j.ecolind.2019.105982.; Lacoursière­Roussel A., Howland K., Normandeau E., Grey E.K., Archambault P., Deiner K., Lodge D.M., Hernandez C., Leduc N., Bernatchez L. eDNA metabarcoding as a new surveillance approach for coastal Arctic biodiversity. Ecol. Evol. 2018;8(16):7763­7777. DOI:10.1002/ece3.4213.; Leray M., Yang J.Y., Meyer C.P., Mills S.C., Agudelo N., Ranwez V., Boehm J.T., Machida R.J. A new versatile primer set targeting a short fragment of the mitochondrial COI region for metabarcoding metazoan diversity: application for characterizing coral reef fish gut contents. Front. Zool. 2013;10(1):34. DOI:10.1186/1742­9994­10­34.; Machida R.J., Leray M., Ho S.­L., Knowlton N. Metazoan mitochondrial gene sequence reference datasets for taxonomic assignment of environmental samples. Sci. Data. 2017;4(1):170027. DOI:10.1038/sdata.2017.27.; Makarchenko E.A., Makarchenko M.A. New findings of chironomids (Diptera, Chironomidae, Orthocladiinae) in Far East and bordering territories. III. Orthocladius van der Wulp. Evraziatskii Entomologicheskii Zhurnal = Euroasian Entomological Journal. 2008; 7(2):243­262. (in Russian); McGoff E., Aroviita J., Pilotto F., Miler O., Solimini A.G., Porst G., Jurca T., Donohue L., Sandin L. Assessing the relationship between the Lake Habitat Survey and littoral macroinvertebrate communities in European lakes. Ecol. Indic. 2013;25:205­214. DOI:10.1016/j.ecolind.2012.09.018.; Meusnier I., Singer G.A.C., Landry J.­F., Hickey D.A., Hebert P.D.N., Hajibabaei M. A universal DNA mini­barcode for biodiversity analysis. BMC Genomics. 2008;9(1):214. DOI:10.1186/1471­2164­9­214.; Moss B., Kosten S., Meerhoff M., Battarbee R.W., Jeppesen E., Mazzeo N., Havens K., Lacerot G., Liu Z., de Meester L., Paerl H., Scheffer M. Allied attack: climate change and eutrophication. Inland Waters. 2011;1(2):101­105. DOI:10.5268/IW­1.2.359.; Nalepa T.F., Fanslow D.L., Lang G.A. Transformation of the offshore benthic community in Lake Michigan: recent shift from the native amphipod Diporeia spp. to the invasive mussel Dreissena rostriformis bugensis. Freshw. Biol. 2009;54(3):466­479. DOI:10.1111/j.1365­2427.2008.02123.x.; Odum Yu. Basic Ecology. Philadelphia–New York–Chicago–San Francisco–Montreal–Toronto–London–Sydney–Tokyo–Mexico City– Rio de Janeiro–Madrid: Saunders College Publ., 1983. (Russ. ed.: Odum Yu. Ekologiya. Moscow, 1986); O’Reilly C.M., Alin S.R., Plisnier P.­D., Cohen A.S., McKee B.A. Climate change decreases aquatic ecosystem productivity of Lake Tanganyika, Africa. Nature. 2003;424(6950):766­768. DOI:10.1038/nature01833.; Porazinska D.L., Giblin­Davis R.M., Faller L., Farmerie W., Kanzaki N., Morris K., Powers T.O., Tucker A.E., Sung W.A.Y., Thomas W.K. Evaluating high­throughput sequencing as a method for metagenomic analysis of nematode diversity. Mol. Ecol. Resour. 2009;9(6):1439­1450. DOI:10.1111/j.1755­0998.2009.02611.x.; Pudovkina T.A., Sitnikova T.Y., Matveyev A.N., Shcherbakov D.Y. Kindred relations of Baikal polychaete of the Manayunkia genus [Polychaeta: Sedentaria: Sabellidae] according to CO1 and settlement history analysis. Russ. J. Genet. Appl. Res. 2016;6(2):129­137. DOI:10.1134/S207905971602009X.; Rezende R.S., Santos A.M., Henke­Oliveira C., Gonçalves J.F., Jr. Effects of spatial and environmental factors on benthic a macroinvertebrate community. Zoologia. 2014;31(5):426­434. DOI:10.1590/s1984­46702014005000001.; Semernoy V.P. Oligochaeta of Lake Baikal. Novosibirsk: Nauka Publ., 2004. (in Russian); Timoshkin O.A. Biodiversity of Baikal fauna: state­of­the­art (Preliminary analysis). In: New Scope on Boreal Ecosystems in East Siberia. Proc. of the Intern. Workshop, Kyoto, Japan, 23–25 Nov. 1994. Novosibirsk: Russ. Acad. Sci. Publ. Siberian Branch, 1997;35­76.; van den Berg M.S., Coops H., Noordhuis R., van Schie J., Simons J. Macroinvertebrate communities in relation to submerged vegetation in two Chara­dominated lakes. Hydrobiologia. 1997;342:143­150. DOI:10.1023/A:1017094013491.; Worrall T.P., Dunbar M.J., Extence C.A., Laize C.L.R., Monk W.A., Wood P.J. The identification of hydrological indices for the characterization of macroinvertebrate community response to flow regime variability. Hydrol. Sci. J. 2014;59(3­4):645­658. DOI:10.1080/02626667.2013.825722.; Yu D.W., Ji Y., Emerson B.C., Wang X., Ye C., Yang C., Ding Z. Biodiversity soup: metabarcoding of arthropods for rapid biodiversity assessment and biomonitoring. Methods Ecol. Evol. 2012;3(4):613623. DOI:10.1111/j.2041­-210X.2012.00198.x.; https://vavilov.elpub.ru/jour/article/view/3941

Availability: https://vavilov.elpub.ru/jour/article/view/3941
https://doi.org/10.18699/VJGB-23-80

Targeted high throughput RNA sequencing for detection of gene fusions and gene expression markers in thyroid cancer ; Определение химерных транскриптов и экспрессионных маркеров методом таргетного высокопроизводительного секвенирования при раке щитовидной железы

Authors: V. D. Yakushina, V. V. Strelnikov, T. F. Avdeeva, T. P. Kazubskaya, T. T. Kondratieva, L. V. Lerner, A. V. Lavrov, В. Д. Якушина, В. В. Стрельников, Т. Ф. Авдеева, Т. П. Казубская, Т. Т. Кондратьева, Л. В. Лернер, А. В. Лавров

Contributors: The research was carried out within the state assignment of Ministry of Science and Higher Education of the Russian Federation., Работа выполнена в рамках государственного задания Минобрнауки России для ФГБНУ «МГНЦ».

Source: Medical Genetics; Том 22, № 11 (2023); 47-57 ; Медицинская генетика; Том 22, № 11 (2023); 47-57 ; 2073-7998

Subject Terms: высокопроизводительное секвенирование, gene fusions, 5’/3’ expression imbalance, gene expression markers, high throughput sequencing, химерные гены, 5’/3’ дисбаланс экспрессии, экспрессионные маркеры

File Description: application/pdf

Relation: https://www.medgen-journal.ru/jour/article/view/2374/1753; Pellegriti G., Frasca F., Regalbuto C., et al. Worldwide increasing incidence of thyroid cancer: update on epidemiology and risk factors. J Cancer Epidemiol. 2013;2013:965212. doi:10.1155/2013/965212.; Vigneri R., Malandrino P., Vigneri P. The changing epidemiology of thyroid cancer: why is incidence increasing? Curr Opin Oncol. 2015;27(1):1-7. doi:10.1097/CCO.0000000000000148.; Cooper D.S., Doherty G.M., Haugen B.R., et al. American Thyroid Association (ATA) Guidelines Taskforce on Thyroid Nodules and Differentiated Thyroid Cancer. Revised American Thyroid Association management guidelines for patients with thyroid nodules and differentiated thyroid cancer. Thyroid 2009;19:1167–214.; Pacini F., Castagna M.G., Brilli L., Pentheroudakis G., ESMO Guidelines Working Group. Thyroid cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol 2012;23(Suppl.7):vii110–9.; Kebebew E., Greenspan F.S., Clark O.H., et al. Anaplastic thyroid carcinoma. Treatment outcome and prognostic factors. Cancer. 2005;103(7):1330-5.; Wendler J., Kroiss M., Gast K., et al. Clinical presentation, treatment and outcome of anaplastic thyroid carcinoma: results of a multicenter study in Germany. Eur J Endocrinol. 2016;175(6):521-529.; Bongiovanni M., Spitale A., Faquin W.C., et al. The Bethesda system for reporting thyroid cytopathology: A meta-analysis. Acta Cytol. 2012;56(4):333-339. doi:10.1159/000339959.; Panebianco F., Nikitski A.V., Nikiforova M.N., et al. Characterization of thyroid cancer driven by known and novel ALK fusions. Endocr Relat Cancer. 2019;26(11):803-814. doi:10.1530/ERC-190325.; Doebele R.C., Drilon A., Paz-Ares L., et al. Entrectinib in patients with advanced or metastatic NTRK fusion-positive solid tumours: integrated analysis of three phase 1-2 trials. Lancet Oncol 2020;21:271-282; National Comprehensive Cancer Network. Thyroid Carcinoma (Version 1.2023). http://www.nccn.org/professionals/physician_gls/pdf/bone.pdf.; Cancer Genome Atlas Research Network. Integrated genomic characterization of papillary thyroid carcinoma. Cell. 2014; 159(3):676690.; Zehir A., Benayed R., Shah R.H., et al. Mutational landscape of metastatic cancer revealed from prospective clinical sequencing of 10,000 patients. Nature Medicine. 2017; 23(6): 703–713.; Rivera M., Ricarte-Filho J., Knauf J., et al. Molecular genotyping of papillary thyroid carcinoma follicular variant according to its histological subtypes (encapsulated vs infiltrative) reveals distinct BRAF and RAS mutation patterns. Mod Pathol. 2010; 23(9):1191–200.; Armstrong M.J., Yang H., Yip L., Ohori N.P., et al. PAX8/PPARγ rearrangement in thyroid nodules predicts follicular-pattern carcinomas, in particular the encapsulated follicular variant of papillary carcinoma. Thyroid. 2014; 24:1369–74.; Nikiforova M.N., Biddinger P.W., Caudill C.M., et al. PAX8-PPARgamma rearrangement in thyroid tumors: RT-PCR and immunohistochemical analyses. Am J Surg Pathol. 2002; 26(8):1016-23.; Ohori N.P., Wolfe J., Hodak S.P., et al. “Colloid-rich” follicular neoplasm/suspicious for follicular neoplasm thyroid fine-needle aspiration specimens: cytologic, histologic, and molecular basis for considering an alternate view. Cancer Cytopathol. 2013; 121(12):718-28.; Landa I., Ibrahimpasic T., Boucai L., et al. Genomic and transcriptomic hallmarks of poorly differentiated and anaplastic thyroid cancers. J Clin Invest. 2016; 126(3):1052-66.; Michuda J., Park B.H., Cummings A.L., et al. Use of clinical RNA-sequencing in the detection of actionable fusions compared to DNA-sequencing alone. Journal of Clinical Oncology 2022; 40:16(suppl): 3077.; Marchiò C., Scaltriti M., Ladanyi M., et al. ESMO recommendations on the standard methods to detect NTRK fusions in daily practice and clinical research. Ann Oncol. 2019;30(9):1417-1427. doi:10.1093/annonc/mdz204.

Availability: https://www.medgen-journal.ru/jour/article/view/2374
https://doi.org/10.25557/2073-7998.2023.11.47-57

Structure and Functioning of Plankton Communities of Phototrophic and Mixotrophic Protists in the Coastal Lagoon “Lake Kislo-Sladkoe” (White Sea, Karelian Coast) ; Структура и функционирование планктонных сообществ фототрофных и миксотрофных протистов в прибрежной лагуне “озеро Кисло-Сладкое” (Белое море, Карельский берег)

Authors: A. O. Plotnikov, E. A. Selivanova, Yu. A. Khlopko, D. A. Voronov, D. N. Matorin, D. A. Todorenko, E. D. Krasnova, А. О. Плотников, Е. А. Селиванова, Ю. А. Хлопко, Д. А. Воронов, Д. Н. Маторин, Д. А. Тодоренко, Е. Д. Краснова

Contributors: The work was carried out under the state budget theme “Diversity, structure and functioning of marine and coastal ecosystems” (CITIS no. 121032500077-8) and Development program of Moscow State University “The future of the planet and global environmental changes.”, Исследование выполнено в рамках государственной темы “Разнообразие, структура и функционирование морских и прибрежных экосистем” (номер ЦИТИС: 121032500077-8), Программы развития МГУ имени М.В. Ломоносова “Будущее планеты и глобальные изменения окружающей среды”.

Source: Izvestiya Rossiiskoi Akademii Nauk. Seriya Geograficheskaya; Том 86, № 6 (2022): Специальный выпуск: Белое море в плейстоцене, голоцене и антропоцене; 985–1001 ; Известия Российской академии наук. Серия географическая; Том 86, № 6 (2022): Специальный выпуск: Белое море в плейстоцене, голоцене и антропоцене; 985–1001 ; 2658-6975 ; 2587-5566

Subject Terms: высокопроизводительное секвенирование, coastal meromictic lakes, separating water bodies, phototrophic protists, phytoplankton, chlorophyll fluorescence, DNA metabarcoding, high-throughput sequencing, прибрежные меромиктические водоемы, отделяющиеся водоемы, фототрофные протисты, фитопланктон, флуоресценция хлорофилла, ДНК метабаркодинг

File Description: application/pdf

Relation: https://izvestia.igras.ru/jour/article/view/1672/905; Белевич Т.А., Ильяш Л.В. Сезонная динамика первичной продукции пикофитопланктона в Кандалакшском заливе Белого моря // Тр. VII Междунар. науч.-практ. конф. “Морские исследования и образование (MARESEDU-2018)”. Тверь: ПолиПРЕСС, 2019. Т. IV. С. 193‒196.; Белевич Т.А., Милютина И.А. Видовое разнообразие фототрофного пикопланктона морей Карского и Лаптевых // Микробиология. 2022. Т. 1. № 1. С. 75‒85. https://doi.org/10.31857/S0026365622010025; Белькова Н.Л. Молекулярно-генетические методы анализа микробных сообществ // Разнообразие микробных сообществ внутренних водоемов России: Учеб.-методич. пособие. Ярославль: Принтхаус, 2009. С. 53‒63.; Ильяш Л.В., Радченко И.Г., Кузнецов Л.Л., Лисицын А.П., Мартынова Д.М., Новигатский А.Н., Чульцова А.Л. Пространственная вариабельность состава, обилия и продукционных характеристик фитопланктона Белого моря в конце лета // Океанология. 2011. Т. 51. № 1. С. 24–32.; Краснова Е.Д. Экология меромиктических озер России. 1. Прибрежные морские водоемы // Водные ресурсы. 2021. Т. 48. № 3. С. 322–333. https://doi.org/10.31857/S0321059621030093; Краснова Е.Д., Воронов Д.А., Демиденко Н.А., Кокрятская Н.М., Пантюлин А.Н., Рогатых Т.А., Самсонов Т.Е., Фролова Н.Л., Шапоренко С.И. К инвентаризации реликтовых водоемов, отделяющихся от Белого моря // Комплексные исследования Бабьего моря, полу-изолированной беломорской лагуны: геология, гидрология, биота – изменения на фоне трансгрессии берегов. Тр. Беломорской биостанции МГУ. М: Тов-во науч. изд. КМК, 2016. Т. 12. С. 211–241.; Краснова Е.Д., Пантюлин А.Н., Маторин Д.Н., Тодоренко Д.А., Белевич Т.А., Милютина И.А., Воронов Д.А. Цветение криптофитовой водоросли Rhodomonas sp. (Cryptophyta, Pyrenomonadaceae) в редокс-зоне водоемов, отделяющихся от Белого моря // Микробиология. 2014. Т. 83. № 3. С. 346–354. https://doi.org/10.7868/S0026365614030100; Лосюк Г.Н., Кокрятская Н.М., Краснова Е.Д. Сероводородное заражение прибрежных озер на разных стадиях изоляции от Белого моря // Океанология. 2021. Т. 61. № 3. С. 401–412. https://doi.org/10.31857/S003015742102012X; Маторин Д.Н., Рубин А.Б. Флуоресценция хлорофилла высших растений и водорослей. М.: Ижевск, 2012. 256 с.; Мордасова Н.В. Косвенная оценка продуктивности вод по содержанию хлорофилла // Тр. ВНИРО. 2014. Т. 152. С. 41‒56.; Нецветаева О.П., Македонская И.Ю., Коробов В.Б., Зметная М.И. Зависимость кислородонасыщения от содержания хлорофилла “а” в поверхностном слое вод Белого моря // Арктика: экология и экономика. 2018. № 3 (31). С. 31‒41. https://doi.org/10.25283/2223-4594-2018-3-31-41; Романенко Ф.А., Шилова О.С. Послеледниковое поднятие Карельского берега Белого моря по данным радиоуглеродного и диатомового анализов озерноболотных отложений п-ова Киндо // ДАН. 2012. Т. 442. № 4. С. 544–548.; Саввичев А.С., Лунина О.Н., Русанов И.И., Захарова Е.Е., Веслополова Е.Ф., Иванов М.В. Микробиологические и изотопно-геохимические исследования озера Кисло-Сладкое − меромиктического водоема на побережье Кандалакшского залива Белого моря // Микробиология. 2014. Т. 83. № 2. С. 191−203. https://doi.org/10.7868/S002636561401011X; Тодоренко Д.А., Краснова Е.Д., Маторин Д.Н. Изучение функционального состояния фотосинтетического аппарата фитопланктона в отделяющихся водоемах на Беломорском побережье с помощью флуоресцентных методов // Тр. VII Междунар. науч.- практ. конф. “Морские исследования и образование (MARESEDU-2018)”. Тверь: ПолиПРЕСС, 2019. Т. IV. С. 227–229.; Чеканов К.А., Краснова Е.Д. Характеристики фотосинтетического аппарата криптофитовых жгутиконосцев Rhodomonas sp. из хемоклина стратифицированной лагуны на Зеленом мысе (Белое море, Кандалакшский залив) // Материалы XXII Междунар. науч. конф. (Школы) по морской геологии “Геология морей и океанов”. М.: ИО РАН, 2019. Т. 3. С. 232–234.; Шапоренко С.И., Корнеева Г.А., Пантюлин А.Н., Перцова Н.М. Особенности экосистем отшнуровывающихся водоемов Кандалакшского залива Белого моря // Водные ресурсы. 2005. Т. 32. № 5. С. 517‒532.; Abad D., Albaina A., Aguirre M., Laza-Martínez A., Uriarte I., Iriarte A., Villate F., Estonba A. Is metabarcoding suitable for estuarine plankton monitoring? A comparative study with microscopy // Marine Biol. 2016. Vol. 163. Iss. 7. Art. number 149. https://doi.org/10.1007/s00227-016-2920-0; Baatar B., Chiang P.-W., Rogozin D.Y., Wu Y.-T., Tseng C.-H., Yang C.-Y., Chiu H.-H., Oyuntsetseg B., Degermendzhy A.G., Tang S.-L. Bacterial Communities of Three Saline Meromictic Lakes in Central Asia // PLOS ONE. 2016. Vol. 11. № 3. e0150847. https://doi.org/10.1371/journal.pone.0150847; Casamayor E.O., Schafer H., Baneras L., Pedros-Alio C., Muyzer G. Identification of and Spatio-Temporal Differences between Microbial Assemblages from Two Neighboring Sulfurous Lakes: Comparison by Microscopy and Denaturing Gradient Gel Electrophoresis // Appl. and Environ. Microbiol. 2000. Vol. 66. № 2. P. 499–508. https://doi.org/10.1128/aem.66.2.499-508.2000; Del Campo J., Pizzorno A., Djebali S., Bouley J., Haller M., Pérez-Vargas J., Lina B., Boivin G., Hamelin M.-E., Nicolas F., Le Vert F., Leverrier Y., Rosa-Calatrava M., Marvel J., Hill F. OVX836 a recombinant nucleoprotein vaccine inducing cellular responses and protective efficacy against multiple influenza A subtypes // NPJ Vaccines. 2019. Vol. 4. Iss. 4. https://doi.org/10.1038/s41541-019-0098-4; Dzhembekova N., Moncheva S., Ivanova P., Slabakova N., Nagai S. Biodiversity of phytoplankton cyst assemblages in surface sediments of the Black Sea based on metabarcoding // Biotechnol. & Biotechnol. Equipment. 2018. Vol. 32. № 6. P. 1507–1513. https://doi.org/10.1080/13102818.2018.1532816; Edgar R.C. Search and clustering orders of magnitude faster than BLAST // Bioinformatics. 2010. Vol. 26. Iss. 19. P. 2460–2461. https://doi.org/10.1093/bioinformatics/btq461; Edgar R.C. UPARSE: highly accurate OTU sequences from microbial amplicon reads // Nature Methods. 2013. Vol. 10. Iss. 10. P. 996–998. https://doi.org/10.1038/nmeth.2604; Falkowski P.G., Raven J.A. Aquatic photosynthesis. USA: Princeton Univ. Press, 2007. 488 p.; Gorlenko V.M., Vainstein M.B., Kachalkin V.I. Microbiological characteristic of lake Mogilnoye // Arch. Hydrobiol. 1978. Vol. 81. № 4. P. 475−492.; Gran-Stadniczeñko S., Egge E., Hostyeva V., Logares R., Eikrem W., Edvardsen B. Protist Diversity and Seasonal Dynamics in Skagerrak Plankton Communities as Revealed by Metabarcoding and Microscopy // J. of Eukaryotic Microbiol. 2018. Vol. 66. Iss. 3. P. 494−513. https://doi.org/10.1111/jeu.12700; Guillou L., Bachar D., Audic S. et al. The Protist Ribosomal Reference database (PR2): a catalog of unicellular eukaryote Small Sub-Unit rRNA sequences with curated taxonomy // Nucleic Acids Res. 2013. Vol. 41. Iss. D1. P. D597–D604. https://doi.org/10.1093/nar/gks1160; Hakala A. Meromixis as a part of lake evolution – observations and a revised classification of true meromictic lakes in Finland // Boreal Environ. Res. 2004. Vol. 9. P. 37–53.; İnceoğlu Ö., Llirós M., Crowe S. A., García-Armisen T., Morana C., Darchambeau F., Borges A.V., Descy J.-P., Servais P. Vertical Distribution of Functional Potential and Active Microbial Communities in Meromictic Lake Kivu // Microbial Ecol. 2015. Vol. 70. Iss. 3. P. 596–611. https://doi.org/10.1007/s00248-015-0612-9; Jeunen G., Lamare M.D., Knapp M., Spencer H.G., Taylor H.R., Stat M., Bunce M., Gemmell N.J. Water stratification in the marine biome restricts vertical environmental DNA (eDNA) signal dispersal // Environ. DNA. 2019. Vol. 2. Iss. 1. P. 99–111. https://doi.org/10.1002/edn3.49; Krasnova E., Matorin D., Belevich T., Efimova L., Kharcheva A., Kokryatskaya N., Losyuk G., Todorenko D., Voronov D., Patsaeva S. The characteristic pattern of multiple colored layers in coastal stratified lakes in the process of separation from the White Sea // Chinese J. of Oceanol. and Limnol. 2018. № 6. P. 1–16. https://doi.org/10.1007/s00343-018-7323-2; Lauro F.M., DeMaere M.Z., Yau S., Brown M.V., Ng C., Wilkins D., Raftery M.J., Gibson J.A., Andrews-Pfannkoch C., Lewis M., Hoffman J.M., Thomas T., Cavicchioli R. An integrative study of a meromictic lake ecosystem in Antarctica // The ISME J. 2010. № 5. P. 879–895. https://doi.org/10.1038/ismej.2010.185; Lewis W.M., Jr. A revised classification of lakes based on mixing // Canadian J. of Fisheries and Aquatic Sci. 1983. Vol. 40. № 10. P. 1779−1787. https://doi.org/10.1139/f83-207; Lunina O.N., Savvichev A.S., Krasnova E.D., Kokryatskaya N.M., Veslopolova E.F., Kuznetsov B.B., Gorlenko V.M. Succession processes in the anoxygenic phototrophic bacterial community in lake Kislo-Sladkoe (Kandalaksha Bay, White Sea) // Microbiology. 2016. Vol. 85. P. 531–544. https://doi.org/10.1134/S0026261716050118; Matorin D., Antal T., Ostrowska M., Rubin A., Ficek D., Majchrowski R. Chlorophyll fluorimetry as a method for studying light absorption by photosynthetic pigments in marine algae // Oceanol. 2004. Vol. 46. № 4. P. 519–531.; Millette N.C., Pierson J.J., Aceves A., Stoecker D.K. Mixotrophy in Heterocapsa rotundata: A mechanism for dominating the winter phytoplankton // Limnol. and Oceanogr. 2017. Vol. 62. Iss. 2. P. 836–845. https://doi.org/10.1002/lno.10470; Orsi W., Song Y.C., Hallam S., Edgcomb V. Effect of oxygen minimum zone formation on communities of marine protists // The ISME J. 2012. № 6. P. 1586–1601. https://doi.org/10.1038/ismej.2012.7; Salmaso N. Effects of Habitat Partitioning on the Distribution of Bacterioplankton in Deep Lakes // Frontiers in Microbiol. 2019. Vol. 10. 2257. https://doi.org/10.3389/fmicb.2019.02257; Savvichev A.S., Babenko V.V., Lunina O.N., Letarova M.A., Boldyreva D.I., Veslopolova E.F., Demidenko N.A., Kokryatskaya N.M., Krasnova E.D., Gaisin V.A., Kostryukova E.S., Gorlenko V.M., Letarov A.V. Sharp water column stratification with an extremely dense microbial population in a small meromictic lake, Trekhtzvetnoe // Environ. Microbiol. 2018. Vol. 20. Iss. 10. P. 3784−3797. https://doi.org/10.1111/1462-2920.14384; Savvichev A.S., Kadnikov V.V., Rusanov I.I. et al. Microbial processes and microbial communities in the water column of the polar meromictic lake Bol’shie Khruslomeny at the White Sea coast // Frontiers in Microbiol. 2020. Vol. 11. 1945. https://doi.org/10.3389/fmicb.2020.01945; Schreiber U. Pulse-Amplitude-Modulation (PAM) Fluorymetry and Saturation Pulse Method: An Overview // Chlorophyll A Fluorescence: A Signature of Photosynthesis / G. Govindjee and G. Papageorgiou (Eds.). Dordrecht: Springer, 2004. P. 279–319. https://doi.org/10.1007/978-1-4020-3218-9; Selivanova E.A., Ignatenko M.E., Yatsenko-Stepanova T.N., Plotnikov A.O. Diatom assemblages of the brackish Bolshaya Samoroda River (Russia) studied via light microscopy and DNA metabarcoding // Protistology. 2019. Vol. 13. Iss. 4. P. 215–235. https://doi.org/10.21685/1680-0826-2019-13-4-5; Suggett D.J., Prašil O., Borowitzka M.A. Chlorophyll a Fluorescence in Aquatic Sciences: Methods and Applications. Dordrecht: Springer, 2011. 326 p. https://doi.org/10.1007/978-90-481-9268-7; Trefault N., De la Iglesia R., Moreno-Pino M., dos Santos A.L., Ribeiro C.G., Parada-Pozo G., Cristi A., Marie D., Vaulot D. Annual phytoplankton dynamics in coastal waters from Fildes Bay, Western Antarctic Peninsula // Sci. Rep. 2021. Vol. 11. 1368. https://doi.org/10.1038/s41598-020-80568-8; Yoshimura S. Abnormal Thermal Stratifications of Inland Lakes // Proceedings of the Imperial Academy. 1937. Vol. 13. P. 316–319. https://doi.org/10.2183/pjab1912.13.316; https://izvestia.igras.ru/jour/article/view/1672

Availability: https://izvestia.igras.ru/jour/article/view/1672
https://doi.org/10.31857/S2587556622060127

Composition of bacterial communities in oil-contaminated bottom sediments of the Kamenka River ; Состав бактериальных сообществ нефтезагрязненных донных отложений реки Каменка

Authors: D. O. Egorova, P. Y. Sannikov, Y. V. Khotyanovskaya, S. A. Buzmakov, Д. О. Егорова, П. Ю. Санников, Ю. В. Хотяновская, С. А. Бузмаков

Contributors: The research was funded by Russian Foundation for Basic Research, project number 20-45-596018 (RFBR competition r_NOTs_Perm region), Исследования выполнены при поддержке Российского фонда фундаментальных исследований (проект №20-45-596018, конкурс РФФИ р_НОЦ_Пермский край)

Source: Vestnik Moskovskogo universiteta. Seriya 16. Biologiya; Том 78, № 1 (2023); 17-24 ; Вестник Московского университета. Серия 16. Биология; Том 78, № 1 (2023); 17-24 ; 0137-0952

Subject Terms: высокопроизводительное секвенирование, oil pollution, bottom sediments, microbial community, high throughput sequencing, нефтяное загрязнение, донные отложения, микробное сообщество

File Description: application/pdf

Relation: https://vestnik-bio-msu.elpub.ru/jour/article/view/1208/613; Johnston J.E., Lim E., Roh H. Impact of upstream oil extraction and environmental public health: a review of the evidence // Sci. Total. Environ. 2019. Vol. 657. P. 187–199.; Костарев С.М. Формирование техногенных скоплений компонентов глубинных флюидов в приповерхностных массивах горных пород (на примере районов нефтедобычи Пермской области) // Известия ВУЗов. Нефть и газ. 2004. № 5. C. 132–143.; Костарев С.М., Бачурин Б.А., Одинцова Т.А. Методические проблемы оценки нефтяного загрязнения подземных вод // Нефтепромысловое дело. 2016. № 12. С. 52–56; Rodríguez-Urine M.L., Peña-Cabriales J.J., RiveraCruz M.C., Délano-Frier J.P. Native bacteria isolated from weathered petroleum oil-contaminated soils in Tabasco, Mexico, accelerate the degradation petroleum hydrocarbons in saline soil microcosms // Env. Tech. Innov. 2021. Vol. 23: 101781.; Kingston P. Long-term environmental impact of oil spills // Spill. Sci. Technol. Bull. 2002. Vol. 7. N 1–2. P. 53–61.; Fahrenfeld N.L., Reyes H.D., Eramo A., Akob D.M., Mumford A.C., Cozzarelli I.M. Shifts in microbial community structure and function in surface waters impacted by unconventional oil and gas wastewater revealed by metagenomics // Sci. Total Environ. 2016. Vol. 580. P. 1205–1213.; Avona A., Capadici M., Trapani D.Di., Giustra M.G., Lucchina P.G., Lumia L., Di Bella G., Rossetti S., Tonazi B., Viviani G. Hydrocarbons removal from real marine sediments: Analysis of degradation pathways and microbial community development during // Sci. Total Environ. 2022. Vol. 838: 156458.; Shaoping K., Zhiwewi D., Bingchen W., Huihui W., Jialiang L., Hongbo S. Changes of sensitive microbial community in oil polluted soil in the coastal area in Shandong, China for ecorestoration // Ecotox. Environ. Saf. 2021. Vol. 207: 111551.; Khan M.A.I., Biswas B., Smith E., Mahmud S.A., Hasan N.A., Khan M.A.W., Naidu R., Megharaj M. Microbial diversity changes with rhizosphere and hydrocarbons in contrasting soils // Ecotox. Environ. Saf. 2018. Vol. 156. P. 434–442; Liu Q., Tang J., Gao K., Gurav R., Giesy J.P. Aerobic degradation of crude oil by microorganisms in soils from four geographic regions of China // Sci. Rep. 2017. Vol. 7: 14856.; Huang L., Te J., Jiang K., Wang Y., Li Y. Oil contamination drives the transformation of soil microbial communities: Co-occurrence pattern, metabolic enzymes and culturable // Ecotox. Environ. Saf. 2021. Vol. 225: 112740.; Зырин Н.Г., Орлов Д.С. Физико-химические методы исследования почв. М.: Изд-во Моск. ун-та, 1964. 348 с.; Bates S.T., Berg-Lyons J.G., Caporaso W.A., Walters W.A., Knight R., Fierer N. Examining the global distribution of dominant archaeal populations in soil // ISME J. 2010. Vol. 5. N 5. Р. 908–917.; Callahan B.J., McMurdie P.J., Rosen M.J., Han A.W., Johnson A.J.A., Holmes S.P. DADA2: Highresolution sample inference from Illumina amplicon data // Nat. Methods. 2016. Vol. 13. N 7. P. 581–583.; McMurdie P.J., Holmes S. phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data // PLoS One. 2013. Vol. 8. N 4: e61217; Wright E.S. Using DECIPHER v2.0 to Analyze big biological sequence data in R // R J. 2016. Vol. 8. N. 1. P. 352–359.; Caporaso J.G, Kuczynski J., Stombaugh J. et. al. QIIME allows analysis of highthroughput community sequencing data // Nat. Methods. 2010. Vol. 7. N 5. P. 335–336.; King G.M., Kostka J.E., Hazen T.C., Sobecky P.A. Microbial responses to the deepwater horizon oil spill: from coastal wetlands to the deep sea // Ann. Rev. Mar. Sci. 2015. Vol. 7. P. 377–401.; Cabello-Yeves P.J., Callieri C., Picazo A., Mehrshad M., Haro-Moreno J.M., Roda-Garcia J.J., Dzhembekova N., Slabakova V., Slabakova N., Moncheva S., Rodriguez-Valera F. The microbiome of the Black Sea water column analyzed by shotgun and genome centric metagenomics // Environ. Microbiol. 2021. Vol. 16: 5.; Schwab L., Popp D., Nowack G., Bombach P., Vogt C., Richnow H.H. Structural analysis of microbiomes from salt caverns used for underground gas storage // Int. J. Hydrogen Energy. 2022. Vol. 47. N 47. P. 20684–20694.; Gillan D.C., Danis B. The archaebacterial communities in Antarctic bathypelagic sediments // DeepSea Res. II. 2007. Vol. 54. N 16–17. P. 1682–1690.; Ganesan M., Mani R., Sai S., Kasivelu G., Awasthi M.K., Rajagopal R., Azelee N.I.W., Selvi P.K., Chang S.W., Ravindra B. Bioremediation by oil degrading marine bacteria: An overview of supplements and pathways in key processes // Chemosphere. 2022. Vol. 303: 134956.; Hou Y., Li S., Dong W., Yuan Y., Wang Y., Shen W., Li J., Cui Z. Community structure of a propanil-degrading consortium and the metabolic pathway of Microbacterium sp. Strain T4-7 // Int. Biodeter. Biodegrad. 2015. Vol. 105. P. 80–89.; Iminova L., Delegan Y., Frantsuzova E., Bogun A., Zvonarev A., Suzina N., Anbumani S., Solyanikova I. Physiological and biochemical characterization and genome analysis of Rhodococcus qingshengii strain 7B capable of crude oil degradation and plant stimulation // Biotech. Rep. 2022. Vol. 35: e00741.; Petrikov K., Delegan Y., Surin A., Ponamoreva O., Puntus I., Filonov A., Boronin A. Glycolipids of Pseudomonas and Rhodococcus oil-degrading bacteria used in bioremediation preparations: formation and structure // Proc. Biochem. 2013. Vol. 48. N 5–6. P. 931–935.; Ma Y., Wang L., Shao Z. Pseudomonas, the dominant polycyclic aromatic hydrocarbon-degrading bacteria isolated from Antarctic soils and the role of large plasmids in horizontal gene transfer // Environ. Microbiol. 2006. Vol. 8. N 3. P. 455–465.

Availability: https://vestnik-bio-msu.elpub.ru/jour/article/view/1208
https://doi.org/10.55959/MSU0137-0952-16-78-1-3

Mutation spectrum in sarcomeric protein genes and their phenotypic features in Belarusian patients with hypertrophic cardiomyopathy

Source: Nauchno-prakticheskii zhurnal «Medicinskaia genetika». :21-33

Subject Terms: высокопроизводительное секвенирование (NGS), phenotypic features, sarcomeric protein genes, TNNС1, MYL3, next generation sequencing (NGS), мутации, hypertrophic cardiomyopathy, mutations, MYL2, 3. Good health, TPM1, MYBPC3, MYH7, гипертрофическая кардиомиопатия, гены белков саркомеров, ACTC1, фенотипические проявления, 10. No inequality

Access URL: https://www.medgen-journal.ru/jour/article/download/691/426
https://www.medgen-journal.ru/jour/article/view/691

Mutation profile of diffuse large B-cell lymphoma with relapses in the central nervous system ; Мутационный профиль диффузной В-крупноклеточной лимфомы с рецидивами в центральной нервной системе

Authors: Voropaeva E.N., Pospelova T.I., Karpova V.S., Churkina M.I., Vyatkin Y.V., Ageeva T.A., Maksimov V.N.

Contributors: The work was performed with the financial support of the grant of the President of the Russian Federation to young scientists MD-2706.2019.7. The work was carried out within the framework of the budget topic under the State task No. AAAAA-A17-117112850280-2., Работа выполнена при финансовой поддержке гранта Президента РФ молодым ученым МД-2706.2019.7. Работа выполнена в рамках бюджетной темы по Государственному заданию № АААА-А17-117112850280-2.

Source: Advances in Molecular Oncology; Vol 9, No 3 (2022); 69-84 ; Успехи молекулярной онкологии; Vol 9, No 3 (2022); 69-84 ; 2413-3787 ; 2313-805X

Subject Terms: lymphoma, mutational profile, high-throughput sequencing, relapse, NF-kB signaling pathway, JAK-STAT signaling pathway, ТР53 gene, chromatin remodeling, immunological control, diffuse large B-cell lymphoma, central nervous system, лимфома, мутационный профиль, высокопроизводительное секвенирование, рецидив, сигнальный путь NF-kB, сигнальный путь JAK-STAT, ген ТР53, ремоделирование хроматина, иммунологический контроль, центральная нервная система, диффузная в-клеточная крупноклеточная лимфома

File Description: application/pdf

Relation: https://umo.abvpress.ru/jour/article/view/460/272; https://umo.abvpress.ru/jour/article/view/460

Availability: https://umo.abvpress.ru/jour/article/view/460
https://doi.org/10.17650/2313-805X-2022-9-3-69-84

Development of quantitative criteria for assessing epidemic potential of the natural-focal viral infections ; Разработка критериев количественной оценки эпидемического потенциала природно-очаговых инфекций вирусной этиологии

Authors: Safonova M.V., Simonova E.G., Lopatin A.A., Dolgova A.S., Dedkov V.G.

Contributors: 0

Source: Russian Journal of Infection and Immunity; Vol 12, No 4 (2022); 745-754 ; Инфекция и иммунитет; Vol 12, No 4 (2022); 745-754 ; 2313-7398 ; 2220-7619

Subject Terms: epidemic potential, epidemic risk, Kemerovo virus, Great Island virus group, genetic diversity, high-throughput sequencing, эпидемический потенциал, эпидемиологический риск, вирус Кемерово, группа вирусов Грейт Айленд, генетическое разнообразие, высокопроизводительное секвенирование

File Description: application/pdf

Relation: https://iimmun.ru/iimm/article/view/1926/1502; https://iimmun.ru/iimm/article/view/1926/1556; https://iimmun.ru/iimm/article/downloadSuppFile/1926/7875; https://iimmun.ru/iimm/article/downloadSuppFile/1926/7876; https://iimmun.ru/iimm/article/downloadSuppFile/1926/7877; https://iimmun.ru/iimm/article/downloadSuppFile/1926/7878; https://iimmun.ru/iimm/article/downloadSuppFile/1926/7879; https://iimmun.ru/iimm/article/downloadSuppFile/1926/7880; https://iimmun.ru/iimm/article/downloadSuppFile/1926/7881; https://iimmun.ru/iimm/article/downloadSuppFile/1926/7882; https://iimmun.ru/iimm/article/downloadSuppFile/1926/8435; https://iimmun.ru/iimm/article/view/1926

Availability: https://iimmun.ru/iimm/article/view/1926
https://doi.org/10.15789/2220-7619-DOQ-1926

Analysis of kefir grains from different regions of the planet using high-throughput sequencing ; Анализ кефирных зерен из разных регионов планеты с применением высокопроизводительного секвенирования

Authors: F. Ding, A. A. Krasilnikova, M. R. Leontieva, L. G. Stoyanova, A. I. Netrusov, Ф. Дин, А. А. Красильникова, М. Р. Леонтьева, Л. Г. Стоянова, А. И. Нетрусов

Source: Vestnik Moskovskogo universiteta. Seriya 16. Biologiya; Том 77, № 4 (2022); 266-272 ; Вестник Московского университета. Серия 16. Биология; Том 77, № 4 (2022); 266-272 ; 0137-0952

Subject Terms: высокопроизводительное секвенирование, kefir grains, lactobacilli, microbiome, high-performance sequencing, кефирные зерна, лактобактерии, микробиом

File Description: application/pdf

Relation: https://vestnik-bio-msu.elpub.ru/jour/article/view/1188/608; Farag M.A., Jomaa S.A., El-Wahed A.A. The many faces of kefir fermented dairy products: quality characteristics, flavour chemistry, nutritional value, health benefits, and safety // Nutrients. 2020. Vol. 12. N 2. P. 346–359.; Nejati F., Junne S., Neubauer P. A big world in small grain: a review of natural milk Kefir starters // Microorganisms. 2020. Vol. 8. N 2: 192.; Khokhlacheva A.A., Egorova M.A., Kalinina A.N., Gradova N.B. Trophic patterns of functioning and microbial profile of an evolutionarily established associative culture of kefir grains // Microbiology. 2015. Vol. 84. N 4. P. 466–447.; Radhouani H., Goncalves C., Maia F.R., Oliveira J.M., Reis R.L. Biological performance of a promising kefiran-biopolymer with potential in regenerative medicine applications: a comparative study with hyaluronic acid // J. Mater. Sci. Mater. Med. 2018. Vol. 29. N 8: 124.; Kotova I.B., Cherdyntseva T.A., Netrusov A.I. Russian kefir grains microbial composition and its changes during production process // Advances in microbiology, infectious diseases and public health, vol. 932 / Ed. G. Donelli. Cham: Springer, 2016. P. 93–102.; Wang S.Y., Chen K.N., Lo Y.M., Chiang M.L., Chen H.C., Liu J.R., Chen M.J. Investigation of microorganisms involved in biosynthesis of the kefir grain // Food Microbiol. 2012. Vol. 3. N 2. P. 274–285.; Zajšek K., Kolar M., Goršek A. Characterisation of the exopolysaccharide kefiran produced by lactic acid bacteria entrapped within natural kefir grains // Int. J. Dairy Technol. 2011. Vol. 6. N 4. P. 544–548.; Diosma G., Romanin D.E., Rey-Burusco M.F., Londero A., Garrote G.L. Yeasts from kefir grains: isolation, identification, and probiotic characterization // World J. Microbiol. Biotechnol. 2014. Vol. 30. N 1. P. 43–53.; Zanirati D.F., Abatemarco M., Cicco Sandesb S.H., Nicolia J.R., Nunes A.C., Neumanna E. Selection of lactic acid bacteria from Brazilian kefir grains for potential use as starter or probiotic cultures // Anaеrobe. 2015. Vol. 3. N 2. P. 70–76.; Amorim F.G., Coitinho L.B., Dias A.T., Friques A.G.F., Monteiro B.L., de Rezende L.C.D., Pereira T.D.M.C., Campagnaro B.P., De Pauw E., Vasquez E.C., Quinton L. Identification of new bioactive peptides from Kefir milk through proteopeptidomics: bioprospection of antihypertensive molecules // Food Chem. 2019. Vol. 28. N 2. P. 109–119.; Cotârleț M., Vasile A.M., Cantaragiu A.M., Gaspar- Pintiliescu A., Crăciunescu O., Oancea A., Moraru A., Moraru I., Bahrim G.E. Colostrum-derived bioactive peptides obtained by fermentation with kefir grains enriched with selected yeasts // Ann. Univ. Dunarea Jos Galati Fascicle VI: Food Technol. 2019. Vol. 4. N 3. P. 54–68.; Ahmed Z., Wang Y., Ahmad A., Khan S. T., Nisa M., Ahmad H. Kefir and health: a contemporary perspective // Crit. Rev. Food Sci. Nutr. 2013. Vol. 5. N 3. P. 422–434.; Fadrosh D.W., Ma B., Gajer P., Sengamalay N., Ott S., Brotman R.M., Ravel J. An improved dual-indexing approach for multiplexed 16S rRNA gene sequencing on the Illumina MiSeq platform // Microbiome. 2014. Vol. 24. N 2. P. 16–25.; Hugerth L.W., Wefer H.A., Lundin S., Jakobsson H.E., Lindberg M., Rodin S., Engstrand L., Andersson A.F. DegePrime, a program for degenerate primer design for broad-taxonomic-range PCR in microbial ecology studies // Appl. Environ. Microbiol. 2014. Vol. 80. N 16. P. 5116–5123.; Merkel A.Yu., Tarnovetskii I.Yu., Podosokorskaya O.A., Toshchakov S.V. Analysis of 16S rRNA primer systems for profiling of thermophilic microbial communities // Microbiology. 2019. Vol. 13. N 6. P. 671–680.; Bolyen E., Rideout J.R., Dillon M.R., et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2 // Nat. Biotechnol. 2019. Vol. 37. N 8. P. 852–857.; Bokulich N.A., Mills D.A. Improved selection of internal transcribed spacer-specific primers enables quantitative, ultra-high-throughput profiling of fungal communities // Appl. Environ. Microbiol. 2013. Vol. 79. N 8. P. 2519–2526.; Willger S.D., Grim S.L., Dolben E.L., Shipunova A., Hampton T.H., Morrison H.G., Filkins L.M., O‘Toole G.A., Moulton L.A., Ashare A., Sogin M.L., Hogan D.A. Characterization and quantification of the fungal microbiome in serial samples from individuals with cystic fibrosis // Microbiome. 2014. Vol. 2. N 1: 40.; Edgar R.C. UPARSE: highly accurate OTU sequences from microbial amplicon reads // Nat. Methods. 2013. Vol. 10. N 10. P. 996–998. 20. Dannemiller K.C., Reeves D., Bibby K., Yamamoto N., Peccia J. Fungal high-throughput taxonomic identifi FHiTINGS) // J. Basic Microbiol. 2014. Vol. 5. N 4. P. 315–321.; Caporaso J.G., Kuczynski J., Stombaugh J., et al. QIIME allows analysis of high-throughput community sequencing data // Nat. Methods. 2010. Vol. 7. N 5. P. 335–336.; Jianzhong Z., Xiaoli L., Hanhu J., Mingsheng D. Analysis of the microflora in Tibetan kefir grains using denaturing gradient gel electrophoresis // Food Microbiol. 2009. Vol. 26. N 8. P. 770–775.; Gao J., Gu F., Abdella N. H., Ruan H., He G. Investigation on culturable microflora in Tibetan kefir grains from different areas of China // J. Food Sci. 2012. Vol. 77. N 8. P. 425–433.; Zheng Y., Lu Y., Wang J., Yang L., Pan C., Huang Y. Probiotic properties of Lactobacillus strains isolated from Tibetan Kefir grains // PLoS One. 2013. Vol. 8: e69868.; Lopitz-Otsoa F., Rementeria A., Elguezabala N., Garaizar J. Kefir: a simbiotic yeasts-bacteria community with alleged healthy capabilities // Rev. Iberoam. Micol. 2006. Vol. 23. N 1. P. 67–74.

Availability: https://vestnik-bio-msu.elpub.ru/jour/article/view/1188
https://doi.org/10.55959/MSU0137-0952-16-2022-77-4-266-272

Genetic variants, clinical characteristics and outcomes of non-compact cardiomyopathy ; Генетические варианты, клиническая характеристика и исходы некомпактной кардиомиопатии

Authors: S. M. Komissarova, N. M. Rineiskaya, N. N. Chakova, A. A. Efimova, T. V. Dolmatovich, S. S. Niyazova, С. М. Комиссарова, Н. М. Ринейская, Н. Н. Чакова, А. А. Ефимова, Т. В. Долматович, С. С. Ниязова

Source: Siberian Journal of Clinical and Experimental Medicine; Том 38, № 2 (2023); 156-165 ; Сибирский журнал клинической и экспериментальной медицины; Том 38, № 2 (2023); 156-165 ; 2713-265X ; 2713-2927

Subject Terms: высокопроизводительное секвенирование (NGS), genotype-phenotype correlation, cardiac magnetic resonance imaging, high-throughput sequencing (NGS), генотип-фенотип корреляции, магнитно-резонансная томография

File Description: application/pdf

Relation: https://www.sibjcem.ru/jour/article/view/1580/750; Oechslin E.N., Attenhofer Jost C.H., Rojas J.R., Kaufmann P.A., Jenni R. Long-term follow-up of 34 adults with isolated left ventricular noncompaction: a distinct cardiomyopathy with poor prognosis. J. Am. Coll. Cardiol. 2000;36(2):493–500. DOI:10.1016/s0735-1097(00)00755-5.; Oechslin E., Jenni R. Left ventricular non-compaction revisited: a distinct phenotype with genetic heterogeneity? Eur. Heart J. 2011;32(12):1446–1456. DOI:10.1093/eurheartj/ehq508.; Towbin J.A., Lorts A., Jefferies J.L. Left ventricular non-compaction cardiomyopathy. Lancet. 2015;386(9995):813–825. DOI:10.1016/S0140-6736(14)61282-4.; Cortés M., Oliva M.R., Orejas M., Navas M.A., Rábago R.M., Martínez M.E. et al. Usefulness of speckle myocardial imaging modalities for differential diagnosis of left ventricular non-compaction of the myocardium. Int. J. Cardiol. 2016;223:813–818. DOI:10.1016/j.ijcard.2016.08.278.; Van Waning J.I., Caliskan K., Michels M., Schinkel A.F.L., Hirsch A., Dalinghaus M. et al. Cardiac phenotypes, genetics, and risk familiar noncompaction cardiomyopathy. J. Am. Coll. Cardiol. 2019;73(13):1601–1611. DOI:10.1016/j.jacc.2018.12.085.; Jefferies J.L. Barth syndrome. Am. J. Med. Genet. Semin. Med. Genet. 2013;163(3):198–205. DOI:10.1002/ajmg.c.31372.; Jenni R., Oechslin E., Schneider J., Attenhofer Jost C., Kaufmann P.A. Echocardiographic and pathoanatomical characteristics of isolated left ventricular non-compaction: A step towards classification as a distinct cardiomyopathy. Heart. 2001;86(6):666–671. DOI:10.1136/heart.86.6.666.; Petersen S.E., Selvanayagam J.B., Wiesmann F., Robson M.D., Francis J.M., Anderson R.H. et al. Left ventricular non-compaction: insights from cardiovascular magnetic resonance imaging. J. Am. Coll. Cardiol. 2005;46(1):101–105. DOI:10.1016/j.jacc.2005.03.045.; Jacquier A., Thuny F., Jop B., Giorgi R., Cohen F., Gaubert J.Y. et al. Measurement of trabeculated left ventricular mass using cardiac magnetic resonance imaging in the diagnosis of left ventricular non-compaction. Eur. Heart J. 2010;31(9):1098–104. DOI:10.1093/eurheartj/ehp595.; Wang K., Li M., Hakonarson H. ANNOVAR: Functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 2010;38(16);e164. DOI:10.1093/nar/gkq603.; Richards S., Aziz N., Bale S., Bick D., Das S., Gastier-Foster J. et al. ACMG Laboratory Quality Assurance Committee. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet. Med. 2015;17(5):405–424. DOI:10.1038/gim.2015.30.; Miszalski-Jamka K., Jefferies J.L., Mazur W., Głowacki J., Hu J., Lazar M. et al. Novel genetic triggers and genotype-phenotype correlations in patients with left ventricular noncompaction. Circ. Cardiovasc. Genet. 2017;10(4):e001763. DOI:10.1161/CIRCGENETICS.117.001763.; Casas G., Limeres J., Oristrell G., Gutierrez-Garcia L., Andreini D., Borregan M. et al. Clinical risk prediction in patients with left ventricular myocardial noncompaction. J. Am. Coll. Cardiol. 2021;78(7):643–662. DOI:10.1016/j.jacc.2021.06.016.; https://www.sibjcem.ru/jour/article/view/1580

Availability: https://www.sibjcem.ru/jour/article/view/1580
https://doi.org/10.29001/2073-8552-2023-38-2-156-165

Analysis of mutations in CDC27, CTBP2, HYDIN and KMT5A genes in carotid paragangliomas

Authors: E. N. Lukyanova, A. V. Snezhkina, D. V. Kalinin, A. V. Pokrovsky, A. L. Golovyuk, O. A. Stepanov, E. A. Pudova, G. S. Razmakhaev, M. V. Orlova, A. P. Polyakov, M. V. Kiseleva, A. D. Kaprin, A. V. Kudryavtseva

Source: Вавиловский журнал генетики и селекции, Vol 22, Iss 6, Pp 726-733 (2018)
Vavilovskii Zhurnal Genetiki i Selektsii

Subject Terms: 0301 basic medicine, мутационная нагрузка, high-throughput sequencing, QH426-470, мутации, высокопроизводительное секвенирование, mutations, carotid paragangliomas, 3. Good health, 03 medical and health sciences, Genetics, экзом, каротидные параганглиомы, mutation load, exome

Access URL: https://vavilov.elpub.ru/jour/article/download/1659/1123
https://doaj.org/article/ef0fbefbfd6b43439f7e3c2701551b67
https://openrepository.ru/article?id=245164
https://vavilov.elpub.ru/jour/article/download/1659/1123
https://vavilov.elpub.ru/jour/article/view/1659

Prevalence of well-characterized and putative marker mutations in benign and malignant thyroid neoplasms ; Распространенность известных и предполагаемых маркерных мутаций при доброкачественных и злокачественных новообразованиях щитовидной железы

Authors: V. D. Yakushina, T. F. Avdeeva, T. P. Kazubskaya, T. T. Kondrat’Ieva, L. V. Lerner, A. V. Lavrov, В. Д. Якушина, Т. Ф. Авдеева, Т. П. Казубская, Т. Т. Кондратьева, Л. В. Лернер, А. В. Лавров

Source: Medical Genetics; Том 20, № 5 (2021); 48-54 ; Медицинская генетика; Том 20, № 5 (2021); 48-54 ; 2073-7998

Subject Terms: дифференциальная диагностика, mutations, rearrangements, targeted high-throughput sequencing, differential diagnostics, мутации, перестройки, таргетное высокопроизводительное секвенирование

File Description: application/pdf

Relation: https://www.medgen-journal.ru/jour/article/view/1912/1492; Sanabria A., Kowalski L.P., Shah J.P., et al. Growing incidence of thyroid carcinoma in recent years: Factors underlying overdiagnosis. Head Neck 2018;40:855-66. doi:10.1002/hed.25029; Haugen B.R., Alexander E.K., Bible K.C., et al. 2015 American Thyroid Association Management Guidelines for Adult Patients with Thyroid Nodules and Differentiated Thyroid Cancer: The American Thyroid Association Guidelines Task Force on Thyroid Nodules and Differentiated Thyroid Cancer. Thyroid. 2016;26(1):1-133. doi:10.1089/thy.2015.0020; Cibas E.S., Ali S.Z. The 2017 Bethesda System for Reporting Thyroid Cytopathology. Thyroid. 2017;27(11):1341-1346. doi:10.1089/thy.2017.0500; Rogers W.A., Craig W.L., Entwistle V.A. Ethical issues raised by thyroid cancer overdiagnosis: A matter for public health?. Bioethics. 2017;31(8):590-598. doi:10.1111/bioe.12383; Rahman S.T., McLeod D.S.A., Pandeya N., et al. Understanding Pathways to the Diagnosis of Thyroid Cancer: Are There Ways We Can Reduce Over-Diagnosis?. Thyroid. 2019;29(3):341-348. doi:10.1089/thy.2018.0570; Cancer Genome Atlas Research Network. Integrated genomic characterization of papillary thyroid carcinoma. Cell. 2014;159(3):676-690. doi:10.1016/j.cell.2014.09.050; Kasaian K., Wiseman S.M., Walker B.A. et al. The genomic and transcriptomic landscape of anaplastic thyroid cancer: implications for therapy. BMC Cancer. 2015;15:984. Published 2015 Dec 18. doi:10.1186/s12885-015-1955-9; Kunstman J.W., Juhlin C.C., Goh G., et al. Characterization of the mutational landscape of anaplastic thyroid cancer via whole-exome sequencing. Hum Mol Genet. 2015;24(8):2318-2329. doi:10.1093/hmg/ddu749; Landa I., Ibrahimpasic T., Boucai L., et al. Genomic and transcriptomic hallmarks of poorly differentiated and anaplastic thyroid cancers. J Clin Invest. 2016;126(3):1052-1066. doi:10.1172/JCI85271; Swierniak M., Pfeifer A., Stokowy T., et al. Somatic mutation profiling of follicular thyroid cancer by next generation sequencing. Mol Cell Endocrinol. 2016;433:130-137. doi:10.1016/j.mce.2016.06.007; Yoo S.K., Lee S., Kim S.J., et al. Comprehensive Analysis of the Transcriptional and Mutational Landscape of Follicular and Papillary Thyroid Cancers. PLoS Genet. 2016;12(8):e1006239. Published 2016 Aug 5. doi:10.1371/journal.pgen.1006239; Pozdeyev N., Gay L.M., Sokol E.S., et al. Genetic Analysis of 779 Advanced Differentiated and Anaplastic Thyroid Cancers. Clin Cancer Res. 2018;24(13):3059-3068. doi:10.1158/1078-0432.CCR-18-0373; Li H., Durbin R. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics. 2010; 26: 589-595.; Van der Auwera G.A., Carneiro M.O., Hartl C., et al. From FastQ data to high confidence variant calls: the Genome Analysis Toolkit best practices pipeline. Curr Protoc Bioinformatics. 2013;43(1110):11.10.1-11.10.33. doi:10.1002/0471250953.bi1110s43; Boeva V., Popova T., Lienard M., et al. Multi-factor data normalization enables the detection of copy number aberrations in amplicon sequencing data. Bioinformatics. 2014;30(24):3443-3450. doi:10.1093/bioinformatics/btu436; Li M.M., Datto M., Duncavage E.J., et al. Standards and Guidelines for the Interpretation and Reporting of Sequence Variants in Cancer: A Joint Consensus Recommendation of the Association for Molecular Pathology, American Society of Clinical Oncology, and College of American Pathologists. J Mol Diagn. 2017;19(1):4-23. doi:10.1016/j.jmoldx.2016.10.002; Paschke R., Cantara S., Crescenzi A., et al. European Thyroid Association Guidelines regarding Thyroid Nodule Molecular Fine-Needle Aspiration Cytology Diagnostics. Eur Thyroid J. 2017;6(3):115-129. doi:10.1159/000468519; Melo M., da Rocha A.G., Vinagre J., et al. TERT promoter mutations are a major indicator of poor outcome in differentiated thyroid carcinomas. J Clin Endocrinol Metab 2014;99:E754-65. doi:10.1210/jc.2013-3734; Bournaud C., Descotes F., Decaussin-Petrucci M., et al. TERT promoter mutations identify a high-risk group in metastasis-free advanced thyroid carcinoma. Eur J Cancer. 2019;108:41-49. doi:10.1016/j.ejca.2018.12.003; Karunamurthy A., Panebianco F., Hsiao S.J., et al. Prevalence and phenotypic correlations of EIF1AX mutations in thyroid nodules. Endocr Relat Cancer. 2016;23(4):295-301. doi:10.1530/ERC-16-0043

Availability: https://www.medgen-journal.ru/jour/article/view/1912
https://doi.org/10.25557/2073-7998.2021.05.48-54

Multiple mutations in associated with LQTS genes in patients with life-threating ventricular tachyarrhythmias ; Множественные мутации в генах, ассоциированных с синдромом LQTS, у пациентов с жизнеугрожающими желудочковыми тахиаритмиями

Authors: N. . Chakova, S. . Komissarova, S. . Niyazova, T. . Dolmatovich, E. . Rebeko, Н. Н. Чакова, С. М. Комиссарова, С. С. Ниязова, Т. В. Долматович, Е. С. Ребеко

Source: Medical Genetics; Том 19, № 12 (2020); 47-55 ; Медицинская генетика; Том 19, № 12 (2020); 47-55 ; 2073-7998

Subject Terms: фенотипические проявления, multiple mutations, next generation sequencing (NGS), phenotypic manifestations, множественные мутации, высокопроизводительное секвенирование (NGS)

File Description: application/pdf

Relation: https://www.medgen-journal.ru/jour/article/view/1815/1448; Schwartz P.J., Crotti L., Insolia R. Long-QT syndrome: from genetics to management Circ Arrhythm Electrophysiol 2012; 5(4): 868-877. doi:10.1161/CIRCEP.111.962019.; Giudicessi J.R., Ackerman M.J. Genotype- and phenotype-guided management of congenital long QT syndrome. Curr Probl Cardiol 2013; 38(10): 417-455. doi:10.1016/j.cpcardiol.2013.08.001.; Ackerman M.J., Priori S.G., Willems S. et al. HRS/EHRA expert consensus statement on the state of genetic testing for the channelopathies and cardiomyopathies this document was developed as a partnership between the Heart Rhythm Society (HRS) and the European Heart Rhythm Association (EHRA). Heart Rhythm 2011; 8(8): 1308-1339. doi:10.1016/j.hrthm.2011.05.020.; Mohler P.J., Schott J.J., Gramolini A.O. et al. Ankyrin-B mutation causes type 4 long-QT cardiac arrhythmia and sudden cardiac death. Nature. 2003; 421(6923): 634-639. doi:10.1038/nature01335.; Wu G., Ai T., Kim J.J. et al. Alpha-1-syntrophin mutation and the long-QT syndrome: a disease of sodium channel disruption. Circ Arrhythm Electrophysiol 2008; 1(3): 193-201. doi:10.1161/CIRCEP.108.769224.; Napolitano C., Priori S.G., Schwartz P.J. et al. Genetic testing in the long QT syndrome: development and validation of an efficient approach to genotyping in clinical practice. JAMA 2005; 294(23): 2975-2980. doi:10.1001/jama.294.23.2975.; Ackerman M.J., Tester D.J., Jones G.S. et al. Ethnic differences in cardiac potassium channel variants: implications for genetic susceptibility to sudden cardiac death and genetic testing for congenital long QT syndrome. Mayo Clin Proc 2003; 78(12): 1479-1487. doi:10.4065/78.12.1479.; Nishio Y., Makiyama T., Itoh H. et al. D85N, a KCNE1 polymorphism, is a disease-causing gene variant in long QT syndrome. J Am Coll Cardiol 2009; 54(9): 812-819. doi:10.1016/j.jacc.2009.06.005.; Husser D., Ueberham L., Hindricks G. et al. Rare variants in genes encoding the cardiac sodium channel and associated compounds and their impact on outcome of catheter ablation of atrial fibrillation. PLoS One 2017; 12(8): e0183690. doi:10.1371/journal.pone.0183690.; Hashemi S.M., Hund T.J., Mohler P.J. Cardiac ankyrins in health and disease. J Mol Cell Cardiol 2009; 47(2): 203-209. doi:10.1016/j.yjmcc.2009.04.010.; Ichikawa M., Aiba T., Ohno S. et al. Phenotypic Variability of ANK2 Mutations in Patients With Inherited Primary Arrhythmia Syndromes. Circ J 2016; 80(12): 2435-2442. doi:10.1253/circj.CJ-16-0486.; Le Scouarnec S., Bhasin N., Vieyres C. et al. Dysfunction in ankyrin-B-dependent ion channel and transporter targeting causes human sinus node disease. Proc Natl Acad Sci U S A 2008; 105(40): 15617-15622. doi:10.1073/pnas.0805500105.; Mohler P.J., Gramolini A.O., Bennett V. Ankyrins. J. Cell Sci Eur 2002; (115): 1565-1566.; Musa H., Murphy N.P., Curran J. et al. Common human ANK2 variant confers in vivo arrhythmia phenotypes. Heart Rhythm 2016; 13(9): 1932-1940. doi:10.1016/j.hrthm.2016.06.012.; Mohler P.J., Yoon W., Bennett V. Ankyrin-B targets beta2-spectrin to an intracellular compartment in neonatal cardiomyocytes. J Biol Chem 2004; 279(38): 40185-40193. doi:10.1074/jbc.M406018200.; Cheng J., Van Norstrand D.W., Medeiros-Domingo A. et al. Alpha1-syntrophin mutations identified in sudden infant death syndrome cause an increase in late cardiac sodium current. Circ Arrhythm Electrophysiol 2009; 2(6): 667-676. doi:10.1161/CIRCEP.109.891440.; Genetics Home Reference [Электронный ресурс]. Режим доступа: https://ghr.nlm.nih.gov/gene/KCNE1 (дата обращения: 13.06.2020).; Lane C.M., Giudicessi J.R., Ye D. et al. Long QT syndrome type 5-Lite: Defining the clinical phenotype associated with the potentially proarrhythmic p.Asp85Asn-KCNE1 common genetic variant. Heart Rhythm 2018; 15(8): 1223-1230. doi:10.1016/j.hrthm.2018.03.038.

Availability: https://www.medgen-journal.ru/jour/article/view/1815

Metagenomic analysis to identify the causative agents of atypical urogenital tract infections ; Метагеномный анализ для идентификации возбудителей нетипичных инфекций урогенитального тракта

Authors: Kutilin D.S.

Contributors: Работа выполнена при поддержке ООО «Эльген» (конкурс научных проектов «Инновация»), включавшей проведение генетического исследования методом высокопроизводительного секвенирования на платформе Illumina HiSeq 3000.

Source: Russian Journal of Infection and Immunity; Vol 11, No 6 (2021); 1108-1122 ; Инфекция и иммунитет; Vol 11, No 6 (2021); 1108-1122 ; 2313-7398 ; 2220-7619

Subject Terms: urogenital tract, infections, chronic inflammation, high-throughput sequencing, 16S rRNA, discriminant analysis, урогенитальный тракт, инфекции, хроническое воспаление, высокопроизводительное секвенирование, 16S рРНК, дискриминантный анализ

File Description: application/pdf

Relation: https://iimmun.ru/iimm/article/view/1713/1364; https://iimmun.ru/iimm/article/downloadSuppFile/1713/6530; https://iimmun.ru/iimm/article/downloadSuppFile/1713/6531; https://iimmun.ru/iimm/article/downloadSuppFile/1713/6532; https://iimmun.ru/iimm/article/downloadSuppFile/1713/6533; https://iimmun.ru/iimm/article/downloadSuppFile/1713/6534; https://iimmun.ru/iimm/article/downloadSuppFile/1713/6535; https://iimmun.ru/iimm/article/downloadSuppFile/1713/6536; https://iimmun.ru/iimm/article/downloadSuppFile/1713/6537; https://iimmun.ru/iimm/article/downloadSuppFile/1713/6538; https://iimmun.ru/iimm/article/downloadSuppFile/1713/6539; https://iimmun.ru/iimm/article/downloadSuppFile/1713/6540; https://iimmun.ru/iimm/article/downloadSuppFile/1713/6541; https://iimmun.ru/iimm/article/downloadSuppFile/1713/6542; https://iimmun.ru/iimm/article/downloadSuppFile/1713/7074; https://iimmun.ru/iimm/article/downloadSuppFile/1713/7075; https://iimmun.ru/iimm/article/downloadSuppFile/1713/7076; https://iimmun.ru/iimm/article/downloadSuppFile/1713/7077; https://iimmun.ru/iimm/article/downloadSuppFile/1713/7078; https://iimmun.ru/iimm/article/downloadSuppFile/1713/7079; https://iimmun.ru/iimm/article/downloadSuppFile/1713/7158; https://iimmun.ru/iimm/article/view/1713

Availability: https://iimmun.ru/iimm/article/view/1713
https://doi.org/10.15789/2220-7619-MAT-1713

Placental Microbiome: a Paradigm Shift or Flaw in the Methodology? ; Микробиом плаценты: сдвиг парадигмы или несовершенство методологии?

Authors: Shipitsyna E.V.

Contributors: 0

Source: Annals of the Russian academy of medical sciences; Vol 76, No 5 (2021); 436-448 ; Вестник Российской академии медицинских наук; Vol 76, No 5 (2021); 436-448 ; 2414-3545 ; 0869-6047 ; 10.15690/vramn.765

Subject Terms: placental microbiome, fetal microbiome, resident microbiota, high-throughput DNA sequencing, microbial contamination, микробиом плаценты, микробиом плода, резидентная микробиота, высокопроизводительное секвенирование ДНК, микробная контаминация

File Description: application/pdf

Relation: https://vestnikramn.spr-journal.ru/jour/article/view/1489/1516; https://vestnikramn.spr-journal.ru/jour/article/view/1489/1534; https://vestnikramn.spr-journal.ru/jour/article/view/1489/1548; https://vestnikramn.spr-journal.ru/jour/article/downloadSuppFile/1489/1857; https://vestnikramn.spr-journal.ru/jour/article/downloadSuppFile/1489/1858; https://vestnikramn.spr-journal.ru/jour/article/downloadSuppFile/1489/1861; https://vestnikramn.spr-journal.ru/jour/article/downloadSuppFile/1489/1862; https://vestnikramn.spr-journal.ru/jour/article/downloadSuppFile/1489/1863; https://vestnikramn.spr-journal.ru/jour/article/downloadSuppFile/1489/2340; https://vestnikramn.spr-journal.ru/jour/article/downloadSuppFile/1489/2341; https://vestnikramn.spr-journal.ru/jour/article/downloadSuppFile/1489/2342

Availability: https://vestnikramn.spr-journal.ru/jour/article/view/1489
https://doi.org/10.15690/vramn1489

Analysis of mutations in CDC27, CTBP2, HYDIN and KMT5A genes in carotid paragangliomas ; Анализ мутаций в генах CDC27, CTBP2, HYDIN и KMT5A при каротидных параганглиомах

Authors: Lukyanova E.N., Snezhkina A.V., Kalinin D.V., Pokrovsky A.V., Golovyuk A.L., Stepanov O.A., Pudova E.A., Razmakhaev G.S., Orlova M.V., Polyakov A.P., Kiseleva M.V., Kaprin A.D., Kudryavtseva A.V.

Source: Vavilovskii Zhurnal Genetiki i Selektsii

Subject Terms: экзом, exome, carotid paragangliomas, mutation load, mutations, high-throughput sequencing, каротидные параганглиомы, мутационная нагрузка, мутации, высокопроизводительное секвенирование

Relation: https://doi.org/10.18699/VJ18.416; https://openrepository.ru/article?id=245164

Availability: https://openrepository.ru/article?id=245164