Lung cancer is one of the most common types of cancer in the world. Although the mechanism of lungcancer is still unknown, a large number of studies have found a link between gene polymorphisms and the risk of lungcancer. The tumor suppressor p53 plays a crucial role in maintaining genomic stability and tumor prevention. MDM2is a critical regulator of the p53 protein. Despite the importance of p53 pathway in cancer, data on the contributionof SNPs of TP53 (rs1042522) and MDM2 (rs2279744) to the development of lung cancer are very contradictory. A metaanalysisthat collects quantitative data from individual studies and combines their results has the advantage of improvingaccuracy, providing reliable estimates, and resolving those issues in which studies on individual associationsare not effective enough. The aim of this study was to determine whether the TP53 (rs1042522) and MDM2 (rs2279744)polymorphisms confer susceptibility to lung cancer. A meta-analysis was conducted on the associations between theTP53 (rs1042522) and MDM2 (rs2279744) polymorphisms and lung cancer. A total of 51 comparison studies including25,366 patients and 25,239 controls were considered in this meta-analysis. The meta-analysis showed no associationbetween lung cancer and MDM2 (rs2279744) under any model. A noteworthy association of TP53 (rs1042522) withsusceptibility to lung cancer in overall pooled subjects was observed under three different models  and dominant). Stratification by ethnicity indicated an association between the TP53(rs1042522) and lung cancer in Asians and Caucasians. This meta-analysis demonstrates that the TP53 (rs1042522), butnot MDM2 (rs2279744) polymorphism may confer susceptibility to lung cancer. Cancerincidence rate varies in different regions of our planet, so thehighest incidence of lung cancer is observed in Eastern Europeand Central and East Asia .Lung cancer remains one of the most common forms of cancerin the world. Every year World Health Organization (WHO)includes lung cancer in the lists of the leading cause of deathworldwide. Thus, there were 2.1 million cases of lung cancerand 1.8 million deaths in 2018 (http://www.ensembl.org/).A large number of researches have been conducted tostudy the molecular base of lung cancer. One of the riskfactorsfor the development of pulmonary neoplasms isgenes polymorphisms. The main cause of carcinogenesis isdisordersin the regulation of cell cycle control. The tumorsuppressorgene TP53 plays an important role in regulatingthe cell cycle. p53 protein is known as the “guardian of thegenome”. p53 regulates many genes expression in responseto cellular stress induced by various adverse environmentalfactors . This protein plays a key rolein processes such as DNA repair, cell cycle arrest, apoptosisand senescence . MDM2 is a key regulatorof p53 protein activity and degradation. Polymorphicvariantsof the TP53 and MDM2 genes have been found invarious types of cancer, including lung cancer. Analysis ofthe literature data showed that polymorphisms of the TP53Arg72Pro (rs1042522) and MDM2 SNP309 (rs2279744) genescause an increased predisposition to tumor development.The TP53 (rs1042522) gene polymorphism is localized onchromosome 17 position 7676154 Genotype frequency in theCaucasian population GG: 0.074, CC: 0.503, CG: 0.423. Inthe East Asian population, GG: 0.173, CC: 0.345, CG: 0.482, bladder , colorectalcancer  and acute lymphocytic leukemia. However, no association was found betweenTP53 Arg72Pro and the risk of acute myeloid leukemia, oral squamous cell carcinoma , and esophagus cancer .http://www.ensembl.org/).The MDM2 SNP309polymorphism was also found to increase the risk of colorectalcancer , breast cancer  andliver cancer . But there was no associationwith prostate, urinary tract  and stomach.The polymorphic allele of the MDM2 gene rs2279744 islocated at 68808800 position on chromosome 12 Genotypefrequency in the Caucasian population TT: 0.404, GG: 0.113,GT: 0.483. In the East Asian population TT: 0.200, GG: 0.276,GT: 0.524 and MDM2 SNP309 (rs2279744) on the predisposition tothe development of pulmonary neoplasia. It was shown thatthe polymorphism of the TP53 Arg72Pro gene is associatedwith a high risk of small cell lung cancer among Spaniards. Similar data were found fornon-small cell lung cancer in Norwegians and Poles , squamous cell lung cancer in German residents , and lungadenocarcinoma in the Chinese population .Data on the contribution of MDM2 SNP309 to the developmentof lung cancer are very contradictory. Most studies haveshown an association of the MDM2 (rs2279744) mutant allelewith a high risk of lung tissue carcinogenesis . However, Pine et al.(2006) did not find that MDM2 SNP309 is associated withlung neoplasia in the European population.The data on the association of polymorphisms of the TP53genes Arg72Pro (rs1042522) and MDM2 SNP309 (rs2279744)with the development of tumors as a whole are very contradictory.Therefore, it would be interesting to perform a metaanalysison the association of TP53 Arg72Pro (rs1042522)and MDM2 SNP309 (rs2279744) with a risk of developinglung cancer in Asian and European populations.Search strategy. Search for relevant studies was conductedusing online databases, such as Scopus, PubMed and Web ofScience. The search strategy was performed using a combinationof the following keywords: “TP53”, “Murine double minute2” or “MDM2”, “polymorphism”, “SNP”, “rs1042522”,“rs2279744”, “Arg72Pro”, “codon 72 Arg”, “c.215C > G”,“SNP309”, “c.291 T > G” “lung cancer”, “non-small cell lungcancer”, “association”.Inclusion and exclusion criteria. The eligible inclusioncriteria for the meta-analysis were (i) case-control study,(ii) identification of different histological types of lungcancer which was confirmed histologically or pathologically,(iii) having an available genotype for estimating anodds ratio (OR) with 95 % confidence interval (95 % CI),(iv) genotype frequencies in controls were consistent withthose expected from Hardy–Weinberg equilibrium ( p > 0.05).The studies were excluded when (i) they were not casecontrolstudies, (ii) with duplicated data from previous articles,(iii) they were not original articles, e. g. review, (iv) inadequategenotype data were available.Data extraction and quality assessment. Two researchers(O.B. and A.K.) evaluated the eligibility of all retrieved studiesand extracted the pertinent data from the specified publicationsin standardized tables. The extracted data included:(i) the first author name, (ii) publication year, (iii) ethnicity,(iv) lung cancer patients and healthy controls sample size foreach studied polymorphism. Disagreement was resolved byconsulting with a third investigator (R.B.). The study qualitywas assessed in accordance with the Newcastle–OttawaScale (NOS) .Statistical analysis. Hardy–Weinberg equilibrium (HWE)in control population was assessed utilizing the “Calculationof Chi-square test for deviation from Hardy–Weinbergequilibrium”online software (http://www.husdyr.kvl.dk/htm/kc/popgen/genetik/applets/kitest.htm). The statistical analysiswas performed using Comprehensive Meta Analysis version2.2.064 . Estimates weresummarized as ORs with 95 % CIs for each study. The heterogeneitywas evaluated by using the I2 index. An I2 valueof > 50 % was considered to indicate high heterogeneity . The random effects model for analysis was used in case high heterogeneity . Otherwise, the fixed-effectsmodel was used. Publication bias was measured via “Begg’sfunnel plot” and “Egger’s linear regression” method . A two-tailed p-value < 0.05 implied a statisticallysignificant publication bias.Studies included in the meta-analysis1.A total of 531 potential articles were identified from the databasessearch. After 236 duplicate records were removed, atotal of 295 potential articles were reviewed. Amongst thesearticles, 216 were excluded after titles and abstracts review.Afterwards, we excluded 28 studies for no case-control design.Finally, 51 studies with a total of 25,239 controls and25,366 cases that met the inclusion criteria were included inthis meta-analysis 1Supplementary Materials are available in the online version of the paper:http://www.bionet.nsc.ru/vogis/download/pict-2020-24/appx13.pdfCharacteristics of studies included in this meta-analysisA total of 37 articles that examined TP53 (rs1042522) associationwith lung cancer risk were determined. Two of thesearticles included data of two different sets (TP53 (rs1042522)and MDM2 (rs2279744))  and these sets were examined autonomously. Thus,the identified 37 articles encompassed case-controls studiesinvolving 16,229 lung cancer patients and 14,897 controls(Table 1). Among 37 articles, 20 studies were establishedin Asian populations and 17 in Caucasian populations. The genotype frequencies in controls of all studies were consistentwith those expected from HWE ( p > 0.05).Another 14 articles identified MDM2 (rs2279744) associationwith increased lung cancer risk were retrieved (Table 2).These 14 articles encompassed case-controls studies involving9,137 lung cancer patients and 10,342 controls. Among14 articles, 7 studies were established in Asian populationsand 7 in Caucasian populations. The genotype frequenciesin controls of all studies were consistent with those expectedfrom HWE ( p > 0.05).All estimated published articles were executed under accreditedgenotyping methods.Meta-analysis of the relationship betweenthe TP53 (rs1042522) polymorphism and lung cancer risksociatedwith lung cancer . And the association was statisticallysignificant under allele model (G versus C), homozygotemodel (GG versus CC)  and dominant model(GG+GC vs. CC)  ( p < 0.05). A summary ofmeta-analysis findings concerning associations between theTP53 (rs1042522) polymorphism and lung cancer risk isshown in Table 3.Further subgroup analysis was conducted on the associationbetween TP53 (rs1042522) polymorphism and the risk of lungcancer (see Table 3). After stratifying by ethnicity, this metaanalysisindicated an obvious association of TP53 (rs1042522)and lung cancer risk among Caucasians  and among Asians .Meta-analysis of the relationship betweenthe MDM2 (rs2279744) polymorphism and lung cancer riskIn this meta-analysis was shown no association MDM2(rs2279744) polymorphism with lung cancer . A summary ofmeta-analysis findings concerning associations between theMDM2 (rs2279744) polymorphism and lung cancer risk isshown in Table 4. Subgroup analysis detected no associationMDM2 (rs2279744) polymorphism with lung cancer.Between-study heterogeneities were found in all subjectsfor both polymorphisms TP53 (rs1042522) and MDM2(rs2279744) . Because of this the meta-analysiswas designed using “a random effect model” to establishpooled OR and corresponding 95 % CI for all models. Weperformed the meta-regression to explore the potential sourceof between-study. A big problem for meta-analysis is the disproportionatenumber of positive studies that leads to a biasin the publication. The funnel plot indicated some evidence ofpublication bias for Caucasians, but not for Asians in analysisof TP53 (rs1042522) and MDM2 (rs2279744) gene polymorphisms. The publication bias was observedfrom Egger’s test ( p ≤ 0.05) also for Caucasian population.The tumor suppressor gene TP53 (previously named p53),is key regulator of a cell cycle network, apoptosis and DNArepair pathway. TP53 is one of the most carcinogenesis-associatedgenes. There were several studies assessing the effectsof TP53 polymorphisms on the risk of lung cancer, but theresults are very contradictory. For example, no associationsof the TP53 (rs1042522) polymorphism with lung cancerwere found in Jung et al.’s (2008) article. But, increased risk to develop lung cancer was observed in association with thePro/Pro genotype variant in Chowdhury et al.’s (2015) research.Mostaid et al. (2014) found that TP53 Arg72Pro andPro72Pro genotype significantly associated with increasedrelative risk of lung cancer. Our previous study also demonstratedthe association of genotype Arg72Pro of TP53 genewith lung cancer risk . Papadakis etal. (2002) demonstrated that subjects with Arg72Arg genotypeof rs1042522 had significantly increased lung cancer risk. Wecomprehensively searched the up-to-date electronic databasesto reveal the associations between TP53 genetic polymorphisms (rs1042522) and risk of lung cancer. The genome-wideassociation study (GWAS) is very popular method to detect avariation in SNPs with variation in common diseases. In 2017,data from a study of new loci of susceptibility to lung cancerwere published. The study identified RNASET2, SECISBP2L,NRG1, CHRNA2, OFBC1 and RTEL1 as candidate genes associatedwith lung cancer . The polymorphismsof TP53 (rs1042522) and MDM2 (rs2279744) weren’tdetected in this GWAS .A total of 37 case-control comparisons for TP53 (rs1042522) were investigated in this meta-analysis. A noteworthy associationof TP53 (rs1042522) with susceptibility to lung cancer inoverall pooled subjects was observed under three differentmodels: the allele contrast, homozygote contrast (additive)and dominant model. Also, stratification analysis explained astrong evidence of this variant with risk of lung cancer amongAsians and Caucasian under allelic, homozygote (only forCaucasian) and dominant models. Moreover, the Arg72Arggenotype was associated with the obvious protective effect.Compared to TP53, whose role has been widely discussed inlung cancer developing, its main negative modifier – MDM2,has not been sufficiently studied. The data on the associationof polymorphism of MDM2 (rs2279744 or 309T > G) withthe risk of developing lung cancer as well as in the case ofTP53 (rs1042522) are contradictory. Thus, Enokida et al.(2014) did not found any association between polymorphismof MDM2 (rs2279744) and lung cancer risk. Chua et al. (2010)demonstrated that the MDM2 (rs2279744) TT rather than theGG genotype is associated with increased risk of lung cancerin Asian. But, the MDM2 TT genotype was associated witha decreased risk of developing NSCLC compared with thatof the MDM2 GG genotypes in Li G. et al.’s (2006) research.A total of 14 case-control comparisons for MDM2 (rs2279744) wereinvestigated in this meta-analysis. There were no significantassociations between MDM2 (rs2279744) polymorphisms andlung cancer with regard to G allele vs. T allele: OR = 0.86,95 % CI 0.71–1.03, p = 0.1; homozygote model: OR = 0.86,95 % CI 0.71–1.03, p = 0.1; dominant model: OR = 0.90, 95 %CI 0.79–1.02, p = 0.5 and recessive model: OR = 1.10, 95 %CI 0.94–1.22, p = 0.276. The stratification analysis also didnot demonstrate the association of this polymorphism withrisk of lung cancer among Asians and Caucasian under allmodels. Thus, MDM2 (rs2279744) polymorphism does notaffect the risk of developing lung cancer.This meta-analysis has some limitations. First, heterogeneitylevel was high. But we tried to eliminate this effect usinga random effects model rather than a fixed effects model.Publication bias could also have biased the results, as studiesthat produced negative results may not have been published.Despite our use of Egger’s regression test, we cannot eliminatethe possibility of bias. Second, the relative importance of theMDM2 (rs2279744) polymorphism during the developmentof lung cancer may vary between ethnic groups, but we wereonly able to perform ethnic-specific meta-analysis in Asiansand Europeans. Thus, our results are applicable to only theseethnic groups. Therefore, additional studies with other ethnicpopulations are warranted to assess the association betweenMDM2 (rs2279744) polymorphism and the risk of lung cancer.But, the present meta-analysis has also several strengths.We used a strong comprehensive search strategy, and had awell-defined inclusion and exclusion criteria. Reviewers performedthe study selection and extracted data independently.Moreover, we assessed the quality of the included studies bypredefined criteria and the score of included studies was high.Finally, all genotype data extracted from the studies werereported in the study. The advantage of this study over othermeta-analyzes is a more complete review of literature and theinclusion of recent data.In summary, this meta-analysis study indicated evidence ofassociation for TP53 (rs1042522), but not MDM2 (rs2279744)variants with lung cancer based on 51 case-control publishedstudies. Additionally, stratified analysis based on ethnicityobserved an obvious association of TP53 (rs1042522) bothamong Asian and European subjects under allelic, homozygoteand dominant models. However, polymorphism MDM2(rs2279744) may not impart susceptibility to lung cancer ineither Asians or Europeans.The authors declare no conflict of interest.Birgander R., Sjalander A., Rannug A., Alexandrie A.K., SundbergM.I., Seidegard J. P53 polymorphisms and haplotypes in lungcancer. Carcinogenesis. 1995;16(9):2233-2236. DOI 10.1093/carcin/16.9.2233.Bray F., Ferlay J., Soerjomataram I., Siegel R.L., Torre L.A., Jemal A.Global cancer statistics 2018: GLOBOCAN estimates of incidenceand mortality worldwide for 36 cancers in 185 countries. CA CancerJ. Clin. 2018;68:394-424. DOI 10.3322/caac.21492.Bulgakova O., Kussainova A., Kakabayev A., Kausbekova A., BersimbaevR. Association of polymorphism TP53 Arg72Pro with radoninducedlung cancer in the Kazakh population. Vavilovskii ZhurnalGenetiki i Selektsii = Vavilov Journal of Genetics and Breeding.2019;23(5):594-599. DOI 10.18699/VJ19.530.Buyru N., Altinisik J., Isin M., Dalay N. p53 codon 72 polymorphismand HPV status in lung cancer. Med. Sci. Monit. 2008;14(9):CR493-497.Cheng H., Ma B., Jiang R., Wang W., Guo H., Shen N., Li D., Zhao Q.,Wang R., Yi P., Zhao Y., Liu Z., Huang T. Individual and combinedeffects of MDM2 SNP309 and TP53 Arg72Pro on breast cancer risk:an updated meta-analysis. Mol. Biol. Rep. 2012;39(9):9265-9274.DOI 10.1007/s11033-012-1800-z.Chowdhury M.K., Moniruzzaman M., Emran A.A., Mostafa M.G.,Kuddus R.H., Uddin M.A. TP53 codon 72 polymorphisms and lungcancer risk in the Bangladeshi population. Asian Pac. J. CancerPrev. 2015;16(8):3493-3498. DOI 10.7314/apjcp.2015.16.8.3493.Chua H.W., Ng D., Choo S. Effect of MDM2 SNP309 and p53 codon72 polymorphisms on lung cancer risk and survival among nonsmokingChinese women in Singapore. BMC Cancer. 2010;10:88.DOI 10.1186/1471-2407-10-88.Ding H., Dai Y., Ning Zh., Fan N., Wang Zh., Li P., Zhang L., Tao Y.,Wang H. Murine double minute 2 SNP T309G polymorphism andurinary tract cancer risk: a meta-analysis. Medicine .2016;95(12):e2941. DOI 10.1097/MD.0000000000002941.Egger M., Smith G., Schneider M., Minder C. Bias in meta-analysisdetected by a simple, graphical test. BMJ. 1997;315(7109):629‐634.DOI 10.1136/bmj.315.7109.629.Enokida Y., Shimizu K., Kakegawa S., Atsumi J., Takase Y., MiyamaeY., Nagashima T., Ohtaki Y., Kaira K., Sunaga N., Yanagitani N.,Yoshino R., Tsunekawa K., Igai H., Kamiyoshihara M., Usui K.,Lezhava A., Tomizawa Y., Ishikawa T., Murakami M., HayashizakiY., Takeyoshi I. Single-nucleotide polymorphism (c.309T > G)in the MDM2 gene and lung cancer risk. Biomed. Rep. 2014;2(5):719-724. DOI 10.3892/br.2014.305.Fan R., Wu M.T., Miller D., Wain J.C., Kelsey K.T., Wiencke J. Thep53 codon 72 polymorphism and lung cancer risk. Cancer Epidemiol.Biomarkers Prev. 2000;9:1037-1042.Fernández-Rubio A., López-Cima M.F., González-Arriaga P., García-Castro L., Pascual T., Marrón M.G., Tardón A. The TP53 Arg72Propolymorphism and lung cancer risk in a population of NorthernSpain. Lung Cancer. 2008;61(3):309-316. DOI 10.1016/j.lungcan.2008.01.017.Giuliani L., Jaxmar T., Casadio C., Gariglio M., Manna A., D’Antonio D.Detection of oncogenic viruses SV40, BKV, JCV, HCMV, HPV and p53 codon 72 polymorphism in lung carcinoma. Lung Cancer. 2007;57(3):273-281. DOI 10.1016/j.lungcan.2007.02.019.Haronikova L., Olivares-Illana V., Wang L., Karakostis K., Chen S.,Fåhraeus R. The p53 mRNA: an integral part of the cellular stressresponse. Nucleic Acids Res. 2019;47(7):3257-3271. DOI 10.1093/nar/gkz124.Hiraki A., Matsuo K., Hamajima N., Ito H., Hatooka S., Suyama M.,Mitsudomi T., Tajima K. Different risk relations with smoking fornonsmall-cell lung cancer: comparison of TP53 and TP73 genotypes.Asian Pac. J. Cancer Prev. 2003;4:107-112.Hu Z., Ma H., Lu D. Genetic variants in the MDM2 promoter and lungcancer risk in a Chinese population. Int. J. Cancer. 2006;118:1275-1278.Javid J., Mir R., Julka P.K., Ray P.C., Saxena A. Association of p53 andmdm2 in the development and progression of non-small cell lungcancer. Tumour. Biol. 2015;36(7):5425‐5432. DOI 10.1007/s13277-015-3208-6.Jiang D.K., Yao L., Wang W.Zh., Peng B., Ren W.H., Yang X.M., Yu L.TP53 Arg72Pro polymorphism is associated with esophageal cancerrisk: a meta-analysis. World J. Gastroenterol. 2011;17(9):1227-1233. DOI 10.3748/wjg.v17.i9.1227.Jun H.J., Park S.H., Lee W.K. Combined effects of p73 and MDM2polymorphisms on the risk of lung cancer. Mol. Carcinog. 2007;46:100-105. DOI 10.1002/mc.20279.Jung H.Y., Whang Y.M., Sung J.S., Shin H.D., Park B.L., Kim J.S.,Shin S.W., Seo H.Y., Seo J.H., Kim Y.H. Association study of TP53polymorphisms with lung cancer in a Korean population. J. Hum.Genet. 2008;53:508-514. DOI 10.1007/s10038-008-0278-y.Kawajiri K., Nakachi K., Imai K. Germ line polymorphisms of p53and CYP1A1 genes involved in human lung cancer. Carcinogenesis.1993;14:1085-1089. DOI 10.1093/carcin/14.6.1085.Kiyohara C., Horiuchi T., Miyake Y., Takayama K., Nakanishi Y. Cigarettesmoking, TP53 Arg72Pro, TP53BP1 Asp353Glu and the riskof lung cancer in a Japanese population. Oncol. Rep. 2010;23(5):1361-1368. DOI 10.3892/or_00000772.Kohno T., Kunitoh H., Mimaki S. Contribution of the TP53, OGG1,CHRNA3, and HLA-DQA1 genes to the risk for lung squamous cellcarcinoma. J. Thorac. Oncol. 2011;6:813-817. DOI 10.1097/JTO.0b013e3181ee80ef.Lee Y.H. Meta-analysis of genetic association studies. Ann. Lab. Med.2015;35(3):283‐287. DOI 10.3343/alm.2015.35.3.283.Li G., Zhai X., Zhang Z., Chamberlain R.M., Spitz M.R. MDM2 genepromoter polymorphisms and risk of lung cancer: a case-controlanalysis. Carcinogenesis. 2006;27:2028-2033. DOI 10.1093/carcin/bgl047.Li W., Wang S.S., Deng J., Tang J.X. Association of p73 gene G4C14-A4T14 polymorphism and MDM2 gene SNP309 with non-smallcell lung cancer risk in a Chinese population. Oncol. Lett. 2017;14(2):1817-1822. PMID: 28789416. PMCID: PMC5529775. DOI10.3892/ol.2017.6327.Li Y., Chang S.-C., Niu R., Li Y., Chang S.-C., Niu R., Liu L., Crabtree-Ide C.R., Zhao B., Shi J., Han X., Li J., Su J., Cai L., Yu S.,Zhang Z.-F., Mu L. TP53 genetic polymorphisms, interactions withlifestyle factors and lung cancer risk: a case control study in a Chinesepopulation. BMC Cancer. 2013;13:607. DOI 10.1186/1471-2407-13-607.Lind H., Ekstrøm P.O., Ryberg D., Skaug V., Andreassen T. Frequencyof TP53 mutations in relation to Arg72Pro genotypes in non-smallcell lung cancer. Cancer Epidemiol. Biomarkers Prev. 2007;16(10):2077-2081. DOI 10.1158/1055-9965.EPI-07-0153.Lind H., Zienolddiny S., Ekstrom P.O., Skaug V., Haugen A. Associationof a functional polymorphism in the promoter of the MDM2gene with risk of nonsmall cell lung cancer. Int. J. Cancer. 2006;119:718-721. DOI 10.1002/ijc.21872.Liu D., Wang F., Guo X., Wang Q., Wang W., Xu H., Xu G. Associationbetween p53 codon 72 genetic polymorphisms and tobacco useand lung cancer risk in a Chinese population. Mol. Biol. Rep. 2013;40(1):645-649. DOI 10.1007/s11033-012-2103-0.Liu G., Miller D.P., Zhou W., Thurston S.W., Fan R., Xu L.L. Differentialassociation of the codon 72 p53 and GSTM1 polymorphisms onhistological subtype of non-small cell lung carcinoma. Cancer Res.2001;61(24):8718-8722.Liu G., Wheatley-Price P., Zhou W. Genetic polymorphisms of MDM2,cumulative cigarette smoking and nonsmall cell lung cancer risk.Int. J. Cancer. 2008;122:915-918. DOI 10.1002/ijc.23178.Ma Y., Bian J., Cao H. MDM2 SNP309 rs2279744 polymorphism andgastric cancer risk: a meta-analysis. PLoS One. 2013;8(2):e56918.DOI 10.1371/journal.pone.0056918.McKay J.D., Hung R.J., Han Y., Zong X., Carreras-Torres R., ChristianiD.C., Caporaso N.E., … Bossé Y., Chanock S., Brennan P.,Landi M.T., Amos C.I. Large-scale association analysis identifiesnew lung cancer susceptibility loci and heterogeneity in geneticsusceptibility across histological subtypes. Nat. Genet. 2017;49(7):1126-1132. DOI 10.1038/ng.3892.Mechanic L.E., Bowman E.D., Welsh J.A., Khan M.A., Hagiwara N.,Enewold L. Common genetic variation in TP53 is associated withlung cancer risk and prognosis in African Americans and somaticmutations in lung tumors. Cancer Epidemiol. Biomarkers Prev.2007;16(2):214-222. DOI 10.1158/1055-9965.EPI-06-0790.Miller D.P., Liu G., De Vivo I., Lynch T.J., Wain J.C., Su L., ChristianiD.C. Combinations of the variant genotypes of GSTP1, GSTM1,and p53 are associated with an increased lung cancer risk. CancerRes. 2002;62:2819-2823.Mittelstrass K., Sauter W., Rosenberger A. Early onset lung cancer,cigarette smoking and the SNP309 of the murine double minute-2(MDM2) gene. BMC Cancer. 2008;8:113. DOI 10.1186/1471-2407-8-113.Mostaid M.S., Ahmed M.U., Islam M.S., Bin Sayeed M.S., Hasnat A.Lung cancer risk in relation to TP53 codon 47 and codon 72 polymorphismin Bangladeshi population. Tumour Biol. 2014;35(10):10309-10317. DOI 10.1007/s13277-014-2285-2.Murata M., Tagawa M., Kimura M., Kimura H., Watanabe S., Saisho H.Analysis of a germ line polymorphism of the p53 gene in lung cancerpatients: discrete results with smoking history. Carcinogenesis.1996;17(2):261-264. DOI 10.1093/carcin/17.2.261.Nadji S.A., Mahmoodi M., Ziaee A.A., Naghshvar F., Torabizadeh J.,Yahyapour Y. An increased lung cancer risk associated with codon72 polymorphism in the TP53 gene and human papillomavirusinfection in Mazandaran province, Iran. Lung Cancer. 2007;56(2):145-151. DOI 10.1016/j.lungcan.2006.12.006.Nicolai S., Rossi A., Daniele N., Melino G., Annicchiarico-PetruzzelliM., Raschellà G. DNA repair and aging: the impact of the p53family.Aging (Albany NY ). 2015;7(12):1050-1065. DOI 10.18632/aging.100858.Papadakis E.D., Soulitzis N., Spandidos D.A. Association of p53 codon72 polymorphism with advanced lung cancer: the Arg alleleis preferentially retained in tumours arising in Arg/Pro germlineheterozygotes.Br. J. Cancer. 2002;87(9):1013-1018. DOI 10.1038/sj.bjc.6600595.Piao J.M., Kim H.N., Song H.R., Kweon S.S., Choi J.S., Yun W.J.p53 codon 72 polymorphism and the risk of lung cancer in a Koreanpopulation. Lung Cancer. 2011;73(3):264-267. DOI 10.1016/j.lungcan.2010.12.017.Pierce L.M., Sivaraman L., Chang W., Lum A., Donlon T., Seifried A.Relationships of TP53 codon 72 and HRAS1 polymorphisms withlung cancer risk in an ethnically diverse population. Cancer Epidemiol.Biomarkers Prev. 2000;9:1199-1204.Pine S.R., Mechanic L.E., Bowman E.D., Welsh J.A., Chanock S.C.,Shields P.G., Harris C.C. MDM2 SNP309 and SNP354 are notassociatedwith lung cancer risk. Cancer Epidemiol. BiomarkersPrev. 2006;15(8):1559-1561. DOI 10.1158/1055-9965.EPI-06-0217.Popanda O., Edler L., Waas P., Schattenberg T., Butkiewicz D., MuleyT., Dienemann H., Risch A., Bartsch H., Schmezer P. Elevatedrisk of squamous-cell carcinoma of the lung in heavy smokers carryingthe variant alleles of the TP53 Arg72Pro and p21 Ser31Arg polymorphisms. Lung Cancer. 2007;55(1):25-34. DOI 10.1016/j.lungcan.2006.09.006.Qin X., Peng Q., Tang W., Lao X., Chen Zh., Lai H., Deng Y., Mo C.,Sui J., Wu J., Zhai L., Yang Sh., Li Sh., Zhao J. An updated metaanalysison the association of MDM2 SNP309 polymorphism withcolorectal cancer risk. PLoS One. 2013;8(9):e76031. DOI 10.1371/journal.pone.0076031.Ren Y.W., Yin Zh., Wan Y., Guan P., Wu W., Li X., Zhou B. P53Arg72Proand MDM2 SNP309 polymorphisms cooperate to increaselung adenocarcinoma risk in Chinese female non-smokers:a case control study. Asian Pac. J. Cancer Prev. 2013;14(9):5415-5420. DOI 10.7314/apjcp.2013.14.9.5415.Saikia B.J., Das M., Sharma S.K., Sekhon G.S., Zomawia E.,Singh Y.M., Mahanta J., Phukan R.K. Association of a p53 codon 72gene polymorphism with environmental factors and risk of lung cancer:a case control study in Mizoram and Manipur, a high incidenceregion in North East India. Asian Pac. J. Cancer Prev. 2014;15:10653-10658. DOI 10.7314/apjcp.2014.15.24.10653.Sakiyama T., Kohno T., Mimaki S., Ohta T., Yanagitani N., Sobue T.,Kunitoh H., Saito R., Shimizu K., Hirama C., Kimura J., Maeno G.Association of amino acid substitution polymorphisms in DNA repairgenes TP53, POLI, REV1 and LIG4 with lung cancer risk. Int. J.Cancer. 2004;114:730-737. DOI 10.1002/ijc.20790.Sobti R.C., Kaur P., Kaur S., Janmeja A.K., Jindal S.K., Kishan J.Impact of interaction of polymorphic forms of p53 codon 72 andN- acetylation gene (NAT2) on the risk of lung cancer in the NorthIndianpopulation. DNA Cell Biol. 2009;28(9):443-449. DOI10.1089/dna.2008.0797.Souto-García A., Fernández-Somoano A., Pascual T., Álvarez-AvellónS.M., Tardón A. Association of p21 Ser31Arg and p53 Arg72Propolymorphisms with lung cancer risk in CAPUA study. Lung Cancer(Auckl ). 2012;3:69-78. DOI 10.2147/LCTT.S35287.Sreeja L., Syamala V., Raveendran P.B., Santhi S., Madhavan J., AnkathilR. p53 Arg72Pro polymorphism predicts survival outcome inlung cancer patients in Indian population. Cancer Invest. 2009;26:41-46. DOI 10.1080/07357900701638459.Su L., Sai Y., Fan R., Thurston S.W., Miller D.P., Zhou W., Wain J.C.,Lynch T.J., Liu G., Christiani D.C. P53 (codon 72) and P21 (codon31) polymorphisms alter in vivo mRNA expression of p21. LungCancer. 2003;40(3):259‐266. DOI 10.1016/s0169-5002(03)00081-3.Sun Zh., Gao W., Cui G.T. Effect of TP53 rs1042522 on the susceptibilityof patients to oral squamous cell carcinoma and oral leukoplakia:a meta-analysis. BMC Oral Health. 2018;18(1):143. DOI 10.1186/s12903-018-0603-6.Szymanowska A., Jassem E., Dziadziuszko R., Borg A., Limon J.,Kobierska-Gulida G., Rzyman W., Jassem J. Increased risk of nonsmallcell lung cancer and frequency of somatic TP53 gene mutationsin Pro72 carriers of TP53 Arg72Pro polymorphism. Lung Cancer.2006;52(1):9-14. DOI 10.1016/j.lungcan.2005.12.007.Tang T., Song X., Yang Zh., Huang L., Wang W., Tan H. Associationbetween murine double minute 2 T309G polymorphism and risk ofliver cancer. Tumour Biol. 2014;35(11):11353-11357. DOI 10.1007/s13277-014-2432-9.Tian X., Dai Sh., Sun J., Jiang Sh., Jiang Y. Association between TP53Arg72Pro polymorphism and leukemia risk: a meta-analysis of14 case-control studies. Sci. Rep. 2016;6:24097. DOI 10.1038/srep24097.Tian X., Dai Sh., Sun J., Jiang Sh., Jiang Y. The association betweenthe TP53 Arg72Pro polymorphism and colorectal cancer: an updatedmeta-analysis based on 32 studies. Oncotarget. 2017;8(1):1156-1165. DOI 10.18632/oncotarget.13589.To-Figueras J., Gene M., Gomez-Catalan J., Galan C., Firvida J., FuentesM. Glutathione-S-Transferase M1 and codon 72 p53 polymorphismsin a northwestern Mediterranean population and their relationto lung cancer susceptibility. Cancer Epidemiol. BiomarkersPrev. 1996;5(5):337-342.Wang X., Jin L., Cui J., Ma K., Chen X., Li W. Mouse double minute-2homolog (MDM2)-rs2279744 polymorphism associated with lungcancer risk in a Northeastern Chinese population. Thorac. Cancer.2015;6(1):91-96. DOI 10.1111/1759-7714.12153.Wang Y.C., Chen C.Y., Chen S.K., Chang Y.Y., Lin P. p53 codon 72polymorphism in Taiwanese lung cancer patients: association withlung cancer susceptibility and prognosis. Clin. Cancer Res. 1999;5:129-134.Wells G.A., Shea B., O’Connell D., Peterson J., Welch V., Losos M.,Tugwell P. The Newcastle–Ottawa Scale (NOS) for assessing thequality if nonrandomized studies in meta-analyses. Available online:http://www.ohri.ca/programs/clinical_epidemiology/oxford.htm(Accessed on 19 October 2009).Wu X., Zhao H., Amos C.I., Shete S., Makan N., Hong W.K., KadlubarF.F., Spitz M.R. p53 genotypes and haplotypes associated withlung cancer susceptibility and ethnicity. J. Natl. Cancer Inst. 2002;94:681-690. DOI 10.1093/jnci/94.9.681.Xiang B., Mi Y.Y., Li T.F., Liu P.F. Updated meta-analysis of the TP53Arg72Pro polymorphism and gastric cancer risk. Asian Pac. J. CancerPrev. 2012;13(5):1787-1791. DOI 10.7314/apjcp.2012.13.5.1787.Xu T., Xu Z.Ch., Zou Q., Yu B., Huang X.E. P53 Arg72Pro polymorphismand bladder cancer risk – meta-analysis evidence for a link inAsians but not Caucasians. Asian Pac. J. Cancer Prev. 2012;13(5):2349-2354. DOI 10.7314/apjcp.2012.13.5.2349.Zhang F., Li D., Li Y., Li H., Sun J., Li X., Li X. Quantitative assessmentof the association between TP53 Arg72Pro polymorphism andrisk of glioma. Tumour Biol. 2014;35(1):747-751. DOI 10.1007/s13277-013-1101-8.Zhang X., Miao M., Guo Y., Tan W., Zhou Y., Sun T., Wang Y., Lin D.Genetic polymorphisms in cell cycle regulatory genes MDM2 andTP53 are associated with susceptibility to lung cancer. Hum. Mutat.2006;27(1):110-117. DOI 10.1002/humu.20277.Zhuo W., Zhang L., Zhu B., Ling J., Chen Z. Association of MDM2SNP309 variation with lung cancer risk: evidence from 7196 casesand 8456 controls. PLoS One. 2012;7:e41546. DOI 10.1371/journal.pone.0041546.


Complete characterization of bis(1H-indazol-1-yl)methane is given with 1H and 13C NMR, UV/Vis, FTIR, high resolution mass spectrometry and for the first time, single crystal X-ray diffraction. This simple, inexpensive pathway to yield exclusively bis(1H-indazol-1-yl)methane provides synthetic access to further investigate the coordination and potential applications of the family of bis(indazolyl)methanes.Synthetic access to poly(indazolyl)methanes has limited their study despite their structural similarity to the highly investigated chelating poly(pyrazolyl)methanes and their potentially important indazole moiety. Herein is presented a high yielding, one-pot synthesis for the 3 UV/Vis λmax (log ε): 251 (3.54), 260 (3.51), 288 (3.52), 293 (3.52), 299 (3.50). IR (cm−1): 3106 (w), 3060 (m), 2957 (w), 2921 (w), 1617 (m), 1499 (m), 1463 (m), 1439 (w), 1353 (m), 1279 (m), 1197 (s), 1150 (w), 1005 (m), 906 (m), 828 (m), 758 (s), 736 (s).Formation of 2.2.2.2.1.H-indazole and 0.31 mmol of trans-dichlorotetrakis(pyridine)cobalt(III) chloride Cl was synthesized from the previous literature Cl. Complete characterization of 1L is presented including 1H and 13C NMR, UV/Vis, FTIR, high resolution mass spectrometry, and for the first time single crystal X-ray diffraction. Creating synthetic access and diffraction data will allow for expansion of our knowledge on the bis(1H-indazol-1-yl)methane family of ligands to be utilized in future synthetic, mechanistic, chelating and pharmaceutical applications.This article presents on a simple, high yielding one-pot synthesis producing exclusively bis(1Supplementary Information


Oncogene 10.1038/s41388-021-01973-5, published online 3 August 2021Correction to: In this article two text marking errors on the Fig. 3F and Supplementary Fig. The correct figures are given below.The original article has been corrected.Supplementary Fig. 3


Plasmodium parasite fertilization. A recombinant Plasmodium vivax P48/45 (Pvs48/45) protein expressed in Escherichia coli (E. coli) was highly antigenic and immunogenic in experimental animals and elicited specific transmission-blocking (TB) antibodies in a previous pilot study. Here, a similar Pvs48/45 gene was expressed in Chinese Hamster Ovary (CHO) cells and we compared its immunoreactivity with the E. coli product. Specific antibody titers were determined using plasma from Colombian individuals (n=227) living in endemic areas where both P. vivax and P. falciparum are prevalent and from Guatemala (n=54) where P. vivax is highly prevalent. In Colombia, plasma seroprevalence to CHO-rPvs48/45 protein was 46.3%, while for E. coli-rPvs48/45 protein was 36.1% (p<0.001). In Guatemala, the sero prevalence was 24.1% and 14.8% (p<0.001), respectively. Reactivity index (RI) against both proteins showed an age-dependent increase. IgG2 was the predominant subclass and the antibody avidity index evaluated by ELISA ranged between 4-6 mol/L. Ex vivo P. vivax mosquito direct membrane feeding assays (DMFA) performed in presence of study plasmas, displayed significant parasite transmission-blocking (TB), however, there was no direct correlation between antibody titers and oocysts transmission reduction activity (%TRA). Nevertheless, DMFA with CHO rPvs48/45 affinity purified IgG showed a dose response; 90.2% TRA at 100 μg/mL and 71.8% inhibition at 10 μg/mL. In conclusion, the CHO-rPvs48/45 protein was more immunoreactive in most of the malaria endemic places studied, and CHO-rPvs48/45 specific IgG showed functional activity, supporting further testing of the protein vaccine potential.P48/45 is a conserved gametocyte antigen involved in  P. falciparum is highly prevalent in sub-Saharan Africa, both P. falciparum and P. vivax coexist in vast regions of Latin America, Asia, and Oceania, with many countries displaying greater P. vivax prevalence  during the fertilization phase in the mosquito midguts  . These antigens have shown the capacity to elicit specific antibodies capable of blocking parasite transmission to mosquitoes and therefore have been identified as potential TB vaccine candidates  , 11. Othndidates . Among tclinical , 14, 15 clinical –19.Pvs48/45 is a cysteine-rich conserved protein expressed on the gametocyte surface of several Plasmodium species, and is involved in parasite fertilization  analyses. These antibodies also reduce parasite transmission to mosquitoes in ex-vivo direct DMFA  and Guatemala (GUA). Additionally, TB activity of anti-CHO-rPvs48/45 specific IgG was determined by ex-vivo DMFA.lization . A full-t manner . Additioect DMFA . Despiteproteins , 22, andP. vivax and P. falciparum are endemic  at the Centro Internacional de Vacunas  in June 2017 (code CECIV 1506-2017) as well as by the Ethics Committee of the GUA Ministry of Health (CNES-dq-005-2015). Additional approval was obtained in GUA from local community leaders before data collection. Written informed consent (IC) was obtained from each volunteer at enrollment. Minors with ages between 7-18 years signed an informed assent (IA) form, and parents or legal guardians gave the corresponding consent. Donors of P. vivax or P. falciparum infections as determined microscopically and confirmed by qPCR. Whole blood samples (5-15mL) were collected in heparin vacutainer tubes by arm venipuncture, and plasma immediately separated by centrifugation. In GUA, 54 patients with ages between 1-70 years of age (38.9% men) with P. vivax infections diagnosed by thick blood smears and confirmed by qPCR, were recruited by active case surveillance, and blood samples were collected as described above. Plasma samples were kept and stored at -80°C until used for serological characterization and for specific CHO-rPvs48/45 antibody affinity purification.In COL, 227 patients, men (56.8%) and women between 6-84 years of age, were recruited by passive surveillance and included in the study. Subjects were randomly selected among a larger group of patients harboring rPvs48/45 gene was expressed in E. coli, as described before  with sufficient viable cell culture biomass of suspension adapted CHO-Express™ cells . All production cultures (post-transfection) were performed in serum-free, animal protein-free medium (low protein content). A non-malaria related protein, expressed in parallel during the production of the CHO-rPvs48/45 protein, was used as a control production to ensure cell culture and methods accuracy. Each production vessel was verified for critical parameters such as cell culture dynamics and recombinant protein production on samples from day 7 and/or day 14, to confirm the appropriate protein cultures. A total of 150 mg of this antigen was produced after a single purification step on IMAC-FPLC. Two buffer exchanges were performed: one to optimize binding of the protein construct to the IMAC column, and the other one, after elution, to remove excess imidazole. SDS-PAGE analysis of both E. coli- and CHO-rPvs48/45 proteins under both reducing (0.05 mol/L dithiothreitol) and non-reducing conditions together with immunoblot and mass spectrometry (LC-MS/MS) confirmed the protein identity. Immunoblot analysis was carried out using sera (1:200 dilution) of P. vivax semi-immune subjects, plasma from Aotus monkeys previously immunized with the E. coli-rPvs48/45 protein (1:200 dilution), and a E. coli-rPvs48/45 monoclonal antibody; normal human serum was used as control and LC/MS/MS analysis was performed using peptides generated by trypsin digestion. Peptides were separated and analyzed using a Qexactive-HFX coupled to U3000 RSLC (Thermofisher). Mass spectra were processed with MaxQuant (v1.6.10.43) using a database consisting of Uniprot entries of Cricetulus griseus , 250 classical contaminants and the sequence of the construction.The CHO-s™ cells . BrieflyrPvs48/45 proteins’ immunoreactivity, as described before , pH 7.4 at 4°C overnight. After plates were blocked with milk solution 5%, plasma samples diluted at 1:200 were added and incubated for 1 hour followed by incubation with alkaline phosphatase (1:1000) conjugated goat anti-human IgG antibody  for 1 hour. Reactions were revealed with para-nitrophenyl phosphate substrate (p-NPP) (Sigma Aldrich) and read at 405 nm wavelength . Cut-off points for ELISA were calculated as three SD above the mean absorbance value at 405 nm of sera from healthy adult volunteers who had never been exposed to malaria (n=60). The results were also expressed as reactivity index (RI) defined as OD values of tested samples divided by the cut-off value. P-value < 0.05 was considered significant.ELISA was used to determine the two d before , 26. BriP. vivax CHO-rPvs48/45 antibodies with ELISA reactive index > 5.0, as described elsewhere , followed by anti-CHO-rPvs48/45-specific antibodies purification using an NHS-activated Sepharose column  coupled with CHO-rPvs48/45 protein, as described previously. Affinity adsorption was performed using the purified total IgG, and elution fraction was neutralized by 1 mol/L Tris, pH 9.0. Specific IgG was then dialyzed against 1x PBS using an Amicon Ultra-4 Centrifugal Filter Unit (30 kDa membrane EMD Millipore). The final protein concentration of specific IgG was measured by DS-11FX+  and adjusted to 0.5 mg/mL (rPvs48/45-specific antibodies (Elisa Units - EU) as described before  of the CHO-rPvs48/45 recombinant protein competitor. The reaction was incubated for 30 min at RT and the reactivity of the antibody preparation was determined by ELISA as previously described  displaying ELISA reactivity indices (RI) > 5.0 and four plasma sera from the same regions with RI between 2.0-3.0  were selected to determine antibody avidity. Polystyrene microplates were coated with 1 μg/mL of the CHO-rPvs48/45 protein in duplicates. After overnight incubation plates were washed and blocked with 100 μL of PBS with 0.5% Tween (PBS-T) per well, 5% skim milk  for 2 h at room temperature (RT). Specific IgG at 10 μg/mL or plasma samples diluted at 1:200 in PBS-T 2.5% skim milk was added to the plates and incubated for 2h at RT. After washing, plates were incubated with different urea concentrations (from 0 to 7 mol/L) in duplicates for 15 min to determine antibody avidity. The reaction was revealed using an anti-human IgG alkaline phosphatase conjugate as described above. The urea concentration resulting in 50% of the original ELISA units (IC50) was calculated using linear regression  and anti-IgG2 . Then a peroxidase-conjugated goat anti-mouse IgG antibody  was added, and the reaction read at 450 nm.The lsewhere . BrieflyrPvs48/45 specific IgG antibodies at 10, 40, and 100 μg/mL was measured by a DMFA using P. vivax gametocyte-infected blood obtained from malaria patients, as previously described  were subsequently reconstituted with a pool of heat-inactivated male AB+ sera obtained from healthy donors purchased from Sigma (H5667 Sigma-Aldrich Inc) or with test samples. A total of ~100 Anopheles albimanus mosquitoes previously subjected to overnight fasting were fed for 15-20 minutes/cage with this mixture. Mosquito midguts were stained with 2% mercurochrome on day 7 post-feeding, and the number of oocysts per mosquito midgut counted.The TB activity of 143 plasma samples (1:2 dilution), and affinity-purified CHO-escribed . Brieflyp-values <0.05 were considered significant. Antibody responses  for both CHO-rPvs48/45 and E. coli- were compared by Fisher’s exact test. Differences of RI between age groups were analyzed by Kruskal-Wallis, followed by Dunn’s multiple comparison test. Correlation between %TRA of human sera and RI by Spearman test. Avidity (IC50) of P. vivax plasma samples and affinity-purified CHO-rPvs48/45 specific IgG were compared by Mann-Whitney tests , and ey tests .p-value for TRA was calculated using a zero-inflated negative binomial model as previously described (The percentage reduction in mean oocyst count/mosquitoes (TRA) was calculated using the following formula: [(Xc − Xa)/Xc)] × 100, where X is the arithmetic mean oocysts in control (c) and test (a) plasma or IgG. The 95% confidence interval and escribed .E. coli-rPvs48/45 gene without the signal peptide and GPI anchor was sub-cloned in the E. coli system as described elsewhere  inserted to avoid inclusion bodies formation (rPvs48/45 has a shorter thioredoxin fragment (42aa), and a theoretical mass of 51,766.22  of samples and in 32% (n=90) to the E. coli-rPvs48/45 product (p<0.001) . In COL plasmas (n=227) the prevalence of specific antibodies was 46.3% and 36.1% to the CHO and E. coli products, respectively. In contrast, in GUA plasmas (n=54) it was 24.1% and 14.8%, respectively, indicating significant regional differences for both proteins (CHO and E. coli p<0.001). Also, samples from Tierralta, (COL), where P. vivax is highly prevalent , presented an immunoreactivity of 58.8% and 34.3% against the CHO and E. coli proteins, respectively. In contrast, samples from Tumaco, where P. falciparum is more prevalent  than P. vivax , ELISA showed 27.3% and 41.7%, respectively. Significant differences in prevalence among both proteins in samples from COL  and GUA samples (p<0.001) was observed. In contrast, in Tumaco (COL) E. coli was better recognized than CHO (p<0.001) (E. coli protein (p<0.001). In GUA, people with > 2.0 RI were 8% (n=1) and 0% (n=0) to CHO and E. coli protein, respectively. Fisher tests indicated that plasma samples with RI > 2 were significantly more frequent in Colombia than in GUA (p=0.0042) to CHO protein. In contrast, there was no difference between both countries to E. coli protein. To determine the impact of age on the RI, in both COL and GUA, samples were stratified into three groups: 0-14 years/old n=41 (14.6%); 15-30 year/old n=118 (42%); and more than >30 years/old, n=122 (43.4%). The mean RI presented an age-dependent increasing trend (rPvs48/45 protein (p<0.05). Individuals >30 years/old presented a RI to CHO mean of 1.45 whereas to E. coli, the mean was 1.13. Significant differences (p<0.05) were observed in the RI values between children (<15 years/old) and adults (>30) when the E. coli - rPvs48/45 protein was used . Regarding TRA activity, 93 of the 143 (65.03%) plasma samples examined by DMFA displayed >80% TRA; 51samples (54.83%) were reactive to the CHO- and 29 (31.18%) reactive to E. coli-rPvs48/45 protein (p>0.28 and E. coli p>0.63).From the total plasma samples studied (n= 281), ELISA assays indicated the presence of specific antibodies to the full-length CHO-p<0.001) Table 1.Pvs48/45 protein. A total of 40 mg/mL of total IgG was obtained after protein G column purification and 500ug/mL of anti-CHO-rPvs48/45-specific antibodies after Sepharose column purification with specific antibody titers of 62.163 EU  (E. coli-rPvs48/45 proteins (n=22)  using the CHO r2.163 EU . SpecifiE. coli-rPvs48/45 specific IgG and sera samples from malaria-endemic regions were incubated with different concentrations of urea. All data sets fitted into the linear regression model (R2>0.94), and the anti-rPvs48/45 specific IgG presented a similar IC50 (4.1 and 4.5 mol/L respectively) with plasma samples with RI between 2-4  and a slightly higher avidity with the HPV-3031 (5.5 mol/L), P-137 (5.6 mol/L), and P-72 (4.9 mol/L) of plasma samples with RI>5.0, except with the sample MPV-139 (3.9 mol/L)  in studies conducted in several countries in Africa where this species is almost exclusively transmitted and malaria transmission intensity is significantly higher than in Latin America  than in GUA  in the year 2017 . In this regard, in COL, immunoreactivity was higher and more prevalent in areas with the relatively higher transmission, e.g., in Tierralta , Department of Cordoba  the conformational differences between the 3D structures of the two proteins and, thus, recognition of different epitopes, 2) by the additional thioredoxin fragment added to the E. coli protein to improve its expression, 3) by potential glycosylation in the CHO protein.Although both proteins were highly immunoreactive, CHO was significantly better recognized by all age groups, except in Tumaco (COL) where Pvs48/45and nor the additional fragment are recognized by control sera.None of the constructs were recognized by sera from naïve individuals indicating that neither full-length P. falciparum is significantly higher that P. vivax, yet, the response to rPvs48/45 was similar than in Tierralta (COL) and GUA suggesting a parasite cross-reactivity between the orthologous proteins in natural conditions. To better understand the sero-epidemiology of the rPvs48/45, we are currently studying malaria-endemic regions with different P. vivax/P. falciparum proportions.Another intriguing observation is that in Tumaco (COL) the prevalence of rPvs48/45 antibodies which confirmed the important role of this parasite antigen in TB immunity under natural conditions  and a low (~25kDa) molecular weight in the  pattern , 41. HerrPvs48/45 activity is independent of the classical complement; this issue requires further analyses.Although several IgG subclasses may contribute to the overall TB activity, the high prevalence of IgG2 suggests that anti-Pfs48/45 vaccine candidate  at the Centro Internacional de Vacunas  (code CECIV 1506-2017) Ethics Committee of the GUA Ministry of Health (CNES-dq-005-2015). Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.rPvs48/45 analysis: AK and GC. Contributed reagents/materials/analysis tools: MA-H, NC, and SH. Wrote the paper: MA-H, NC, GC, CL, and AK. All authors contributed to the article and approved the submitted version.Conceived and designed the experiments: MA-H and SH. Performed the experiments: NC, CE, KM, ES, AC, JR, and AM. Analyzed the data: MA-H, SH, GC, and CL. LC/MS/MS CHO-NIH/NIAID 1R01AI121237-01 sponsored this study and in part by the Intramural Research Program of NIAID, NIH.https://www.frontiersin.org/articles/10.3389/fimmu.2021.634738/full#supplementary-materialThe Supplementary Material for this article can be found online at: Click here for additional data file.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Pickering S, Batra R, Merrick B, et al. Comparative performance of SARS-CoV-2 lateral flow antigen tests and association with detection of infectious virus in clinical specimens: a single-centre laboratory evaluation study. Lancet Microbe 2021; published online June 30. https://doi.org/10.1016/ S2666-5247(21)00143-9—This Article should have been published under a CC BY Open Access license. This correction has been made as of Aug 3, 2021.


Mutant alleles of the Rht-B1 and Rht-D1 (Reduced height) genes are widely used in bread wheat breeding for the development of intensive-type cultivars. These genes and their f lanking regions have been sequenced and the point mutations leading to the nonsense codons  and various insertions  associated with a change in plant height have been described. DNA-markers based on the allele-specif ic PCR have been developed to identify single-nucleotide changes. However, the use of such technique imposes stringent PCR conditions, and the resulting data are not always unambiguous. An alternative can be found in the CAPS technology: it detects differences in sequences by digesting PCR products. In the absence of restrictases capable of digesting DNA at the point mutation site, restriction sites can be introduced into the primer sequence (derived CAPS). The aim of this study was to propose a system of CAPS-, dCAPS- and STS-markers for identifying alleles of the reduced height genes frequently used in breeding programs. Three CAPS have been developed to identify the Rht-B1b, Rht-D1b, Rht-B1p alleles, as well as two dCAPS for Rht-B1b, Rht-B1e. STS-markers for the insertion-containing alleles Rht-B1c, Rht-B1h and Rht-B1i-1 have been selected from publications. The proposed markers were tested during the genotyping of 11 bread wheat accessions from the VIR collection with the abovementioned mutant alleles and the wild-type Rht-B1a and Rht-D1a. The presence of nonsense mutations was also conf irmed by the resultsof allele-specif ic PCR. This marker system, along with the existing ones, can be used to identify dwarf ing alleles ofthe Rht-B1 and Rht-D1 genes in bread wheat for genetic screening of accessions from ex situ collections and/or formarker-assisted selection. The development of intensive-type short-stemmed wheat cultivarsis considered one of the key success factors in breadwheat breeding, primarily in implementing the Green Revolutioninitiative in the world’s developing countries . The decrease in plant height notonly entailed higher resistance to lodging, with its favorableeffect on the efficiency of mechanized harvesting, but alsoincreased the number of grains per ear and their number per1 m2, which aggregately led to higher yields .At least 25 genes controlling plant height in bread wheat(Triticum aestivum L.) and related species were described: theyare known as Reduced height – Rht1–Rht25. All these genesare in one way or another associated with the growth hormonegibberellin . Some of them,the so-called GA-sensitive genes Rht4–Rht9, Rht12–Rht20 andRht25, are apparently involved in the synthesis or degradationof gibberellic acid (GA). Other genes, GA-insensitive ones,such as Rht-A1, Rht-B1, and Rht-D1, determine the responseto this acid. For some genes , thenature of their response has not yet been clarified .The most widespread among GA-sensitive genes is Rht8,transferred in the early 20th century, together with the closelylinked photoperiod insensitivity allele Ppd-D1a of the Ppdgene (response to photoperiod ), from the Japanese cultivarAkakomugi first to Italian and later to many East and SouthEuropean cultivars . Thisgene does not exert any significant reducing effect on thecoleoptile length and, as a consequence, makes it possibleto sow seeds to a greater depth, which plays a decisive rolein maintaining the viability of seedlings under water deficitsor high temperatures .GA-insensitive genes were studied in more detail; they arelocated on the short arms of chromosomes of homeologousgroup 4 . Dominantalleles of these genes (wild-type) encode DELLA proteins,belonging to the family of GRAS proteins (transcription regulators);at their C-terminus, there is a conservative domainthat can bind to other transcription factors and thereby blocktheir function. That is why large amounts of DELLA proteinsin cells decelerate plant growth. There is a DELLA domain atthe variable N-terminus: it is capable of forming the GA–GID1complex . Thiscomplex undergoes polyubiquitination and degradation inducedby proteasomes. Accordingly, a decrease in the amountof DELLA proteins in cells in the presence of GA reduces theirnegative effect on plant growth .A fairly large number of recessive and semi-dominant mutantalleles altering the stem length in different ways havebeen described for the Rht-B1 and Rht-D1 genes. These alleleshave been sequenced; the most thoroughly studied sequencesare presented by us in Supplementary material 11. The allelesRht- B1b (=Rht1), Rht-B1e ,Rht-B1p (=Rht17) and Rht-D1b (=Rht2) were shown to beassociated with single-nucleotide substitutions that lead tothe formation of premature stop codons . The phenotypic effectof such nonsense mutations varies from moderate  to strong  .http://vavilov.elpub.ru/jour/manager/files/Suppl_Porotnikov_Engl.pdfSupplementary materials 1 and 2 are available in the online version of the paper:The alleles Rht-B1h and Rht-B1i-1 have large (over 100 bp)insertions in the 5′ flanking region, while Rht-B1c (=Rht3)is characterized by the presence of an insertion in the 5′ untranslatedregion identical to that in Rht-B1h and, at the sametime, the presence of the Veju retrotransposon in the codingregion . Such insertions can lead to the formationof nondegradable proteins, so the growth of mutant plants isconstitutively repressed,more significantly than in the caseof nonsense mutations in the N-terminal coding region . For example, the Rht-B1c allelereduces plant height approximately by 60 % . However, insertions can not onlyreduce but also increase the height of plants  as, for example, in the case ofRht-B1i-1 . Besides, the alleles of “strongdwarfing”, Rht-D1c (Rht10) and Rht-D1d (Rht Ai-bian 1a),reducing the height by 60–70 %, were identified in the Rht-D1gene; they turned out to be multiple copies of the mutant alleleRht-D1b . There are also other known allelesof the Rht-B1h–o and Rht-D1e–j genes, associated witheither nucleotide changes (missense mutations) or indels. Theyare identified in a large number of Chinese cultivars using theEcoTILLING method; however, their phenotypic effect hasnot yet been described. Mutant alleles of the Rht-A1 genewere also identified for the first time in Chinese cultivars .The alleles most frequently used in breeding programs areRht-B1b and Rht-D1b. Their source was the Japanese cultivarNorin 10. At the end of the 20th century, more than 70 % ofthe world’s bread wheat cultivars contained these alleles . Later, however, it was shown thattheir occurrence depended on the region of the world. Rht-B1b was detected in 36.2 % of bread wheat cultivars from China,and Rht-D1b in 53.4 % . Meanwhile,the genotyping of 247 cultivars from the United States andCanada helped to identify these alleles in more than 90 %of them . Rht-D1b predominates in thegenotypes of European cultivars, while its occurrence in thecultivars registered after 1990 is 49 % .Widespread in Russia are cultivars with the Rht-B1e allele,obtained by mutagenesis in cv. Bezostaya 1; the mutantform is Krasnodarsky Karlik 1 . At present, semi-dwarf cultivars , homozygous for Rht-B1e alleles,are cultivated both in Russia and the ex-USSR countries onan area of more than 4 million hectares .The allele Rht-B1p is also promising for breeding: a stopcodon emerges in its DELLA domain due to the substitutionof cytosine for thymine at position 178 from the start codon.This mutation causes an up to 30 cm decrease in the heightof bread wheat plants, especially as far as the lower internodeis concerned, but it does not reduce the length of the ear .The sequencing of Rht-B1 and Rht-D1 alleles in variousbread wheat cultivars have led to the development of molecularmarkers for their identification. For example, STS markerswere obtained to identify the insertion-containing allelesRht-B1c, Rht-B1h and Rht-B1i-1 . Markers based on allele-specific PCR(AS-PCR), including real-time AS-PCR, are used to identifythe alleles Rht-B1b, Rht-B1e, Rht-B1p and Rht-D1b, carryingsingle-nucleotide substitutions .The widespread alleles Rht-B1b and Rht-D1b as well asthose of the Rht24 gene are identified on the basis of competitiveallele-specific PCR (KASP-markers), offering a possibilityto evaluate large numbers of bread wheat accessions atlow time costs .It should also be mentioned that AS-PCR results strongly dependon the reaction conditions, require several replicationsof the analysis, and call for strict observance of the author’sprotocol, which is not always possible. The KASP analysis,in its turn, requires sophisticated equipment and expensivereagents, which are often unaffordable to small practice-orientedlaboratories.The use of CAPS (cleaved amplified polymorphic sequence)markers can be an alternative to AS-PCR: they are based onthe presence of a restriction site in the region with a singlenucleotidemutation (the site is absent in the wild type) or,contrariwise, on the disappearance of the site typical of thewild type in the mutant version . If restrictionsites are absent at the locations of the analyzed mutations,they can be produced purposefully through designing modifiedprimers, i. e., by the derived CAPS method, or dCAPS .Unlike AS-PCR, the CAPS and dCAPS marker techniquesare effortlessly reproducible and do not require stringentPCR conditions, while the results of such analysis are easilyinterpreted in agarose gels. It is possible to generate markersusing the basic PCR equipment. Previously, such markers weredeveloped for the Rht24 dwarfing gene .The objective of the present study was to develop CAPS anddCAPS markers for the analysis of single-nucleotide changesin Rht-B1 and Rht-D1, test STS markers for identification ofinsertions in these genes and, as a result, propose a markersystem for identifying the alleles most frequently used inbread wheat breeding.Plant material. Eleven bread wheat accessions from the VIRcollection with known alleles of the Rht-B1 and Rht- D1 dwarfinggenes (Table 1) served as the material for this study. Thecultivars Chinese Spring and Hongdongmai with wild-typealleles Rht-B1a and Rht-D1a were used as controls. Eachof the studied accessions was represented in the genotypingprocess by two or three individual plants as well as by bulkDNA sample, which was isolated from a total of 10–20 genotypes(seedlings).DNA extraction. DNA was extracted from 10-day-oldseedlings using a modified CTAB extraction technique .Sequences alignment. The sequences of different allelesof the Rht-B1 and Rht-D1 genes were aligned using MEGA X(https://www.megasoftware.net/), Unipro UGENE , and BioEdit Sequence Alignment Editor. Restriction sites were searched for using theGenScript Restriction Enzyme Map Analysis Tools .Primers development. Primers for the nested PCR andCAPS analysis were developed with the Primer3Plus software. Primer quality  was monitored using OligoAnalyzerTool, a web resource from Integrated DNA Technologies, Inc.. Primers for dCAPSmarkers were generated using the dCAPS Finder 2.0 software. The primers developed in the courseof this study and those supplied from published sources arepresented in Tables 2 and 3, and their locations are shown inFig. 1, a, b.PCR procedure: a) nested PCR. The nested PCR methodwas applied to enhance the specificity of the dCAPS analysis:the first PCR was performed with primers BF/VIR.B1R flankingthe region of point mutations in the Rht-B1 gene; afterthat, the resulting PCR product was used as a template for thesecond PCR with dCAPS  and CAPS(B1epF/B1pR) primers. The first round of nested PCR wascarried out in 25 μl of the reaction mixture containing 40 ngof total wheat DNA; 1× reaction buffer; 1.5 mM of MgCl2;0.6 mM of each dNTP; 0.25 μM of both forward and reverseprimer, and 1 unit of Taq DNA polymerase . For higher specificity, the PCR programcontained the Touchdown function: the initial annealing temperaturewas 4 degrees higher than the design temperature anddecreased by 0.5 degrees per cycle for 8 cycles (see Table 3).Samples of the resulting amplification products (2 μl ofeach) were transferred into clean tubes, diluted 50 times withwater, and used as a template in the second stage of PCR.Another 10 μL of each PCR product was taken to control the success of PCR by agarose gel electrophoresis .The remainder (approximately 12 μl) was treated with therestriction enzyme BstV1I  to generate the CAPS marker for theRht- B1b allele.The second round of nested PCR was performed in 20 μlof the reaction mixture containing 4 μl of the template; 1×reaction buffer; 2.5 mM of MgCl2; 0.3 mM of each dNTP;0.25 μM of both forward and reverse primer, and 1 unit of TaqDNA polymerase . The programs for each pair of primersare also presented in Table 3. Approximately 12 μl of theamplification mixture were taken for restriction analysis, andthe remainder was used for PCR control by electrophoresis;b) standard PCR. In the cases of CAPS markers for theRht-D1b allele and the markers detecting retrotransposonin the gene’s coding region and insertions in the 5′ flankingregion, PCR was performed under standard conditions. Thereaction mixture (20 μl) contained 40 ng of DNA; 1× reactionbuffer; 2.5 mM of MgCl2; 0.3 mM of each dNTP; 0.25 μMof each primer, and 1 unit of Taq DNA polymerase ;the programs are presented in Tables 2 and 3;с) allele-specific PCR. The conditions and the programs forAS-PCR corresponded to those recommended by the authorsof the primers .Restriction analysis. PCR products were treated with restrictionenzymes produced by SibEnzyme, using the manufacturer’sprotocol (http://russia.sibenzyme.com).Fragment separation was done in horizontal agarosegels in the 1× TBE buffer under the voltage of 5 V/cm. Thegels were stained with ethidium bromide and visualized inUV light.For the development of CAPS and dCAPS markers, thesequences from the NSBI databases were analyzed (https://www.ncbi.nlm.nih.gov/) for the following alleles of the dwarfinggenes: Rht-B1b, Rht-B1e, Rht-B1p and Rht-D1b. Also,the sequences of the wild-type alleles Rht-A1a, Rht-B1a andRht-D1a were retrieved as controls. The Genbank accessionnumbers for used sequences are given in Supplementary material1. Sequence alignment confirmed the presence of nonsensemutations in these allelic forms, which made it possible to startthe development of CAPS and dCAPS markers .A search was made for each nonsense mutation to identifyrestriction sites that would distinguish the target allele fromall others, including wild-type ones. The BstV1I (GCAGC)restriction enzyme, unable to digest the mutant GTAGC site,was selected for Rht-B1b. Similarly, BstHHI (GCGC) becamethe restriction enzyme for the Rht-B1p detection (mutantsite GCGT). On the contrary, the BstSFI restriction enzyme(CTRYAG) exclusively digested the mutant site (CTGTAG)contained in Rht-D1b. Thus, it was possible to develop suchCAPS markers as CB1b/BstV1I, CB1p/BstHHI and CD1b/BstSFI to identify the alleles Rht-B1b, Rht-B1p and Rht-D1b,respectively.We failed to identify restriction sites at the location of thenonsense mutation in the Rht-B1e allele. Hence, the dCAPSmarker dCB1e/HinfI was developed for it: the sequence of thereverse primer was modified so that the analyzed nucleotide,together with the 3′ end of the primer, formed a GATTC restrictionsite, providing an opportunity to distinguish this mutationfrom all other alleles by means of the HinfI restriction. ThedCAPS marker dCB1b/Acc36I was additionally constructedto identify Rht-B1b .When performing PCR under standard conditions, with thegenomic DNA of bread wheat used as a template, we wereunable to obtain specific fragments for the dCAPS markers andthe CAPS marker CB1p/BstHHI (the data are not presented).We therefore applied the nested PCR method: the amplificationproducts of the BF/VIR.B1R primers, flanking the regionof localization of all analyzed point mutations in the Rht-B1gene, were used as a template for the second round .The developed markers were tested on a set of bread wheataccessions with known alleles of the dwarfing genes, and all of them demonstrated high efficiency in differentiating thewild-type Rht-B1a, Rht-D1a and mutant versions Rht-B1b,Rht-B1e, Rht-B1p and Rht-D1b .Concurrently, allele-specific primers retrieved from publishedsources were used to identify nonsense mutations inRht-B1b, Rht-B1e, Rht-B1p and Rht-D1b compared to thewild type . For this purpose, two pairs of primers were usedfor identification of each mutation: one of them detected themutant version, while the other spotted the wild type andall other alleles. It was shown for Rht-B1b, Rht-B1e andRht-D1b that the results of allele-specific PCR on the wholeagreed with the data of CAPS and dCAPS analyses. However,identification of the wild-type Rht-B1a and Rht-D1a alleleswith the primers BF/WR and DF2/WR2, respectively , involved certain difficulties: poor reproducibilityof results, and generation of weakly expressed fragments informs with Rht-B1b and/or Rht-D1b . In the case of Rht-B1p, allele-specific PCR under theconditions of this study turned out to be ineffective: afteramplification with the Rht-B1p-F/R1 primers , a specific product was generated both in the formswith mutant alleles and in those with the wild-type ones .The study also employed five pairs of STS primers  as a tool for identifyingmutations associated with the presence of a retrotransposonin the coding region (Rht-B1c) as well as with insertionsin the promoter region (Rht-B1i-1) and the 5′ flanking region(Rht-B1h). The locations of these insertions are marked in thescheme of the Rht-B1 gene; it also shows primers for theirdetection .Two pairs of primers were used for the Rht-B1i-1 allele : one of them (B1i-MF1/MR1) in the presence ofan insertion produced a specific 330 bp fragment, while theother (B1i-MF2/MR2) amplified fragments of different sizesin genotypes with or without an insertion . Similarly, to detect the Rht-B1h allele, the Rht-B1h.F/R1 primers were used, resulting in a specific productof 247 bp, as well as the Rht-B1h.F/R2 primers, generatingfragments of different sizes  . Since Rht-B1h has a common insertion in the5′ flanking region with Rht-B1c, the Rht-B1c-F1/R1 primer,specific for the retrotransposon sequence, was also used fortheir differentiation  . Additional evidence of the presence of a retrotransposonmay be found in the fact that no PCR productsare generated in genotypes with this insertion during the firstround of nested PCR with the BF/VIR.B1R primers: it can beexplained by a big distance between the primers .Our testing of STS markers showed a complete concordancebetween the presence of their diagnostic fragments and thecomposition of alleles present in the studied genotypes . The accessions Atlas 66 and Zheng 9023 containingRht-B1h yielded amplification products pointing to the presenceof an insertion in the 5′ flanking region. In the accession Triumph carrying the Rht-B1i-1 allele, which increasesplant height, an insertion in the promoter region was detectedusing molecular markers, and in Tom Thumb (Rht-B1c), aretrotransposon in the coding sequence and an insertion inthe 5′ flanking region were found. It should be mentionedthat when a retrotransposon was identified using the Rht-B1c-F1/ R1 primers, in addition to the formation of a fragment ofthe expected size, the emergence of nonspecific products ofa larger size was observed in Tom Thumb (Rht-B1c) and inall other genotypes .Assessing the system of the proposed molecular markersin its entirety, it should be kept in mind that it can be used togenerate a marker profile for each of the studied alleles of theRht-B1 and Rht-D1 genes, i. e., to get an unambiguous answerwhether one of the abovementioned alleles of the Rht-B1 andRht-D1 dwarfing genes is present in one or another genotype.Marker profiles for the alleles are presented in Table 4.As a result of this study, a system of molecular markers wasproposed for the Rht-B1 and Rht-D1 dwarfing genes to identifythe alleles most often used in bread wheat breeding. Thesystem is based on the developed CAPS and dCAPS markersof nonsense mutations in these genes, which were previouslydetected by allele-specific PCR . Five STS markersretrieved from published sources were used to identify insertions.The CAPS and dCAPS markers were tested during the genotypingof bread wheat accessions from the VIR collection,containing the mutant Rht-B1b, Rht-B1c, Rht-B1e, Rht-B1h,Rht-B1i-1, Rht-B1p and Rht-D1b alleles as well as those ofthe wild-type. The tests showed complete concordance ofthe obtained results with the expected ones. The presenceof Rht- B1b, Rht-B1e, Rht-B1p and Rht-D1b was also confirmedby allele-specific PCR with the primers widely usedin research and breeding programs .The main advantage of our molecular marker system liesin good reproducibility of results and their unambiguous interpretation.The CASP/dCAPS analysis faces no problemswith controlling the PCR reaction success, because amplificationproducts are formed in all genotypes, and differencesbetween alleles are pinpointed after treatment with restrictionenzymes. Besides, notwithstanding the high cost of restrictionenzymes, CASP/dCAPS analysis is less expensive, sincethere is no need to perform two independent PCRs in severalreplications to detect each allele. The procedure is conductedemploying standard PCR equipment and using agarose gel electrophoresis, so it can be carried out by small practiceorientedlaboratories. When any new point mutations in theRht-B1 and Rht-D1 dwarfing genes become known, a similarapproach to the development of CAPS/dCAPS markers canbe applied to identify them.The authors declare no conflict of interest.Antonova O.Yu., Klimenko N.S., Rybakov D.A., Fomina N.A., ZheltovaV.V., Novikova L.Yu., Gavrilenko T.A. SSR analysis of modernrussian potato varieties using DNA samples of nomenclatural standards.Biotekhnologiya i Selektsiya Rasteniy = Plant Biotechnologyand Breeding. 2020;3(4):77-96. DOI 10.30901/2658-6266-2020-4- o2. (in Russian)Bazhenov M.S., Divashuk M.G., Amagai Y., Watanabe N., Karlov G.I.Isolation of the dwarfing Rht-B1p (Rht17) gene from wheat and thedevelopment of an allele-specific PCR marker. Mol. Breed. 2015;35(11):1-8. DOI 10.1007/s11032-015-0407-1.Bazhenov M.S., Nazarova L.A., Chernook A.G., Divashuk M.G. Improvedmarker for the Rht-B1p dwarfing allele in wheat. In: CurrentChallenges in Plant Genetics, Genomics, Bioinformatics, andBiotechnology: Proc. of the Fifth International Scientific ConferencePlantGen2019 June 24–29, 2019. Novosibirsk, Russia. Novosibirsk:ICG SB RAS. 2019;190-192. DOI 10.18699/ICG-PlantGen2019-61Borojevic K., Borojevic Ks. The transfer and history of “reduced heightgenes” (Rht) in wheat from Japan to Europe. J. Hered. 2005;96(4):455-459. DOI 10.1093/jhered/esi060.Börner A., Plaschke J., Korzun V., Worland A.J. The relationships betweenthe dwarfing genes of wheat and rye. Euphytica. 1996;89(1):69-75. DOI 10.1007/BF00015721.Divashuk M.G., Bespalova L.A., Vasilyev A.V., Fesenko I.A., PuzyrnayaO.Y., Karlov G.I. Reduced height genes and their importance inwinter wheat cultivars grown in southern Russia. Euphytica. 2013;190(1):137-144. DOI 10.1007/s10681-012-0789-7.Divashuk M.G., Vasilyev A.V., Bespalova L.A., Karlov G.I. Identity ofthe Rht-11 and Rht-B1e reduced plant height genes. Russ. J. Genet.2012;48(7):761-763. DOI 10.1134/S1022795412050055Ellis M.H., Rebetzke G.J., Chandler P., Bonnett D., Spielmeyer W.,Richards R.A. The effect of different height reducing genes on theearly growth of wheat. Funct. Plant Biol. 2004;31(6):583-589. DOI10.1071/FP03207Ellis M.H., Spielmeyer W., Gale K., Rebetzke G., Richards R. “Perfect”markers for the Rht-B1b and Rht-D1b dwarfing genes inwheat. Theor.Appl. Genet. 2002;105(6-7):1038-1042. DOI 10.1007/s00122-002-1048-4.Evans L.T. Feeding the Ten Billion: Plants and Population Growth.Cambridge: Cambridge University Press, 1998.Flintham J.E., Gale M.D. The Tom Thumb dwarfing gene Rht3 inwheat. Theor. Appl. Genet. 1983;66(3-4):249-256. DOI 10.1007/BF00251155.Gale M.D., Marshall G.A. The chromosomal location of Gai 1 andRht 1, genes for gibberellin insensitivity and semi-dwarfism, in aderivative of Norin 10 wheat. Heredity. 1976;37(2):283-289. DOI10.1038/hdy.1976.88Gale M.D., Youssefian S., Russell G.E. Dwarfing genes in wheat. In:Russel G.E. (Ed.). Progress in Plant Breeding. London: Butterworths-Heinemann, 1985;1-35.Grover G., Sharma A., Gill H.S., Srivastava P., Bains N.S. Rht8 geneas an alternate dwarfing gene in elite Indian spring wheat cultivars.PLoS One. 2018;13(6):e0199330. DOI 10.1371/journal.pone.0199330.Guedira M., Brown-Guedira G., Van Sanford D., Sneller C., Souza E.,Marshall D. Distribution of Rht genes in modern and historic winterwheat cultivars from the Eastern and Central USA. Crop Sci. 2010;50(5):1811-1822. DOI 10.2135/cropsci2009.10.0626Hall T. BioEdit: a user-friendly biological sequence alignment editorand analysis program for Windows 95/98/NT. Nucleic Acids Symp.Ser. 1999;41:95-98.Hedden P. The genes of the green revolution. Trends Genet. 2003;19(1):5-9. DOI 10.1016/S0168-9525(02)00009-4.Korzun V., Röder M.S., Ganal M.W., Worland A.J., Law C.N. Geneticanalysis of the dwarfing gene (Rht8) in wheat. Part I. Molecularmapping of Rht8 on the short arm of chromosome 2D of bread wheat(Triticum aestivum L.). Theor. Appl. Genet. 1998;96(8):1104-1109.DOI 10.1007/s001220050845.Kurkiev K.U., Tyryshkin L.G., Kolesova M.A., Kurkiev U.K. Identificationof Rht2 and Rht8 genes for semidwarfness in hexaploidtriticale with use of DNA markers. Vavilovskii Zhurnal Genetikii Selektsii = Vavilov Journal of Genetics and Breeding. 2008;12(3):372-377. (in Russian)Li A., Yang W., Guo X., Liu D., Sun J., Zhang A. Isolation of a gibberellin-insensitive dwarfing gene, Rht-B1e, and development ofan allele-specific PCR marker. Mol. Breed. 2012;30(3):1443-1451.DOI 10.1007/s11032-012-9730-y.Li A., Yang W., Lou X., Liu D., Sun J., Guo X., Wang J., Li Y., Zhan K.,Ling H.Q., Zhang A. Novel natural allelic variations at the Rht-1loci in wheat. J. Integr. Plant Biol. 2013;55(11):1026-1037. DOI10.1111/jipb.12103Lou X., Li X., Li A., Pu M., Shoaib M., Liu D., Sun J., Zhang A.,Yang W. The 160 bp insertion in the promoter of Rht-B1i plays avital role in increasing wheat height. Front. Plant Sci. 2016;7(307):1-13. DOI 10.3389/fpls.2016.00307Lukyanenko P.P., Zhogin A.F. Use of induced dwarf mutants in winterwheat breeding. Selektsiya i Semenovodstvo = Breeding and SeedIndustry. 1974;1:13-17. (in Russian)McIntosh R.A., Dubсovsky J., Rogers W.J., Morris C., Appels R.,Xia X.C. Catalogue of gene symbols for wheat: 2015–2016 supplement.2016. Available at: https://shigen.nig.ac.jp/wheat/komugi/genes/macgene/supplement2015.pdf.McIntosh R.A., Dubсovsky J., Rogers W.J., Xia X.C., Raupp W.J. Catalogueof gene symbols for wheat: 2018 supplement. 2018. Availableat: https://wheat.pw.usda.gov/GG3/sites/default/files/Catalogue%20of %20Gene %20Symbols %20for %20Wheat %20- %20supplement2018-2019.pdf.McIntosh R.A., Yamazaki Y., Dubсovsky J., Rogers J., Morris C., AppelsR., Xia X.C. Catalogue of gene symbols for wheat. 2013. Availableat: https://shigen.nig.ac.jp/wheat/komugi/genes/download.jsp.Neff M.M., Neff J.D., Chory J., Pepper A.E. dCAPS, a simple techniquefor the genetic analysis of single nucleotide polymorphisms:experimental applications in Arabidopsis thaliana genetics. Plant J.1998;14(3):387-392. DOI 10.1046/j.1365-313X.1998.00124.x.Neff M.M., Turk E., Kalishman M. Web-based primer design for singlenucleotide polymorphism analysis. Trends Genet. 2002;18(12):613-615. DOI 10.1016/s0168-9525(02)02820-2.Okonechnikov K., Golosova O., Fursov M. Unipro UGENE: a unifiedbioinformatics toolkit. Bioinformatics. 2012;28(8):1166-1167. DOI10.1093/bioinformatics/bts091.Pearce S., Saville R., Vaughan S.P., Chandler P.M., Wilhelm E.P.,Sparks C.A., Al-Kaff N., Korolev A., Boulton M.I., Phillips A.L.,Hedden P., Nicholson P., Thomas S.G. Molecular characterizationof Rht-1 dwarfing genes in hexaploid wheat. Plant Physiol. 2011;157(4):1820-1831. DOI 10.1104/pp.111.183657Peng J., Richards D.E., Hartley N.M., Murphy G.P., Devos K.M.,Flintham J.E., Beales J., Fish L.J., Worland A.J., Pelica F., SadhakarD., Christou P., Snape J.W., Gale M.D., Harberd N.P. ‘Greenrevolution’ genes encode mutant gibberellin response modulators.Nature. 1999;400(6741):256-261. DOI 10.1038/22307.Pestsova E., Korzun V., Börner A. Validation and utilisation of Rhtdwarfing gene specific. Cereal Res. Commun. 2008;36(2):235-246.DOI 10.1556/CRC.36.2008.2.4Rabinovich S.V. The breeding value of the Krasnodarskiy karlik 1mutant. In: Chemical Mutagenesis in the Creation of Varietieswith New Properties. Moscow: Nauka Publ., 1986;88-92. (in Russian)Rasheed A., Wen W., Gao F., Zhai S., Jin H., Liu J., Guo Q., Zhang Y.,Dreisigacker S., Xia X., He Z. Development and validation of KASP assays for genes underpinning key economic traits in breadwheat. Theor. Appl. Genet. 2016;129(10):1843-1860. DOI 10.1007/s00122-016-2743-x.Shavrukov Y.N. CAPS markers in plant biology. Russ. J. Genet. Appl.Res. 2016;6(3):279-287. DOI 10.1134/S2079059716030114.Sukhikh I.S., Vavilova V.Y., Blinov A.G., Goncharov N.P. Diversityand phenotypical effect of the allele variants of dwarfing Rhtgenes in wheat. Russ. J. Genet. 2021;57(2):127-138. DOI 10.1134/S1022795421020101Thomas S.G. Novel Rht-1 dwarfing genes: tools for wheat breedingand dissecting the function of DELLA proteins. J. Exp. Bot. 2017;68(3):354-358. DOI 10.1093/jxb/erw509.Tian X., Wen W., Xie L., Fu L., Xu D., Fu C., Wang D., Chen X.,Xia X., Chen Q., He Z., Cao S. Molecular mapping of reduced plantheight gene Rht24 in bread wheat. Front. Plant Sci. 2017;8:1-9. DOI10.3389/fpls.2017.01379.Untergasser A., Nijveen H., Rao X., Bisseling T., Geurts R., LeunissenJ.A. Primer3Plus, an enhanced web interface to Primer3. NucleicAcids Res. 2007;35(2):71-74. DOI 10.1093/nar/gkm306.Wen W., Deng Q., Jia H., Wei L., Wei J., Wan H., Yang L., Cao W.,Ma Z. Sequence variations of the partially dominant DELLA geneRht-B1c in wheat and their functional impacts. J. Exp. Bot. 2013;64(11):3299-3312. DOI 10.1093/jxb/ert183.Wilhelm E.P., Mackay I.J., Saville R.J., Korolev A.V., Balfourier F.,Greenland A.J., Boulton M.I., Powell W. Haplotype dictionary forthe Rht-1 loci in wheat. Theor. Appl. Genet. 2013;126(7):1733-1747.DOI 10.1007/s00122-013-2088-7.Wu J., Kong X., Wan J., Liu X., Zhang X., Guo X., Zhou R., Zhao G.,Jing R., Fu X., Jia J. Dominant and pleiotropic effects of a GAIgene in wheat results from a lack of interaction between DELLAand GID1. Plant Physiol. 2011;157(4):2120-2130. DOI 10.1104/pp.111.185272.Würschum T., Langer S.M., Longin C.F.H., Tucker M.R., Leiser W.L.A modern Green Revolution gene for reduced height in wheat.Plant J. 2017;92(5):892-903. DOI 10.1111/tpj.13726.Youssefian S., Kirby E.J.M., Gale M.D. Pleiotropic effects of theGA- insensitive Rht dwarfing genes in wheat. 2. Effects on leaf, stem,ear and floret growth. Field Crops Res. 1992;28(3):191-210. DOI10.1016/0378-4290(92)90040-G.Zhang X., Yang S., Zhou Y., He Z., Xia X. Distribution of the Rht-B1b,Rht-D1b and Rht8 reduced height genes in autumn-sown Chinesewheats detected by molecular markers. Euphytica. 2006;152(1):109-116. DOI 10.1007/s10681-006-9184-6.


Novel coronavirus 2019 (Covid19) caused by SARS-CoV2 can lead to significant morbidity and mortality. There is unclear association between Covid19 and bacteremia. Patient characteristics and outcomes are not well defined. This retrospective cohort study assessed this in patients with Covid19 and bacteremia.Patients with Covid-19 admitted to a tertiary care suburban academic medical center (UH) were assessed retrospectively by EMR chart review for co-morbidities, pre and in hospital factors, and outcomes as defined below. Bacteremias grouped into gram-negative or gram-positive with collation of each unique bacterial species (Table 1).Total 1398 patients with Covid19 hospitalized at UH during local peak of pandemic of whom 238 (17.02%) developed 264 bacteremias with gram-positive  and gram-negative organisms . Relevant characteristics (Table 2) 53% with immunomodulator therapy (steroids/Tocilizumab), mean length of stay 21.04days (SEM ± 1.67) with day SARS-CoV2 PCR positivity -1.15days from hospitalization (SEM ± 0.49) and day initial bacteremia 6.38 (SEM ± 0.77), 55.4% required ICU admission, with 89% ICU admissions requiring mechanical ventilation. Most common co-morbidity  Hypertension 56.3% followed by Obesity (BMI >30) 45.8% and CAD/CHF 40.3%. Laboratory parameters (Table 3)significant for average difference (date bacteremia- date admission) for Procalcitonin 4.15ng/mL , CRP -0.934mg/dL , WBC 7.027 K/uL . These analyses excluded difference of 0 from hospital day 1 bacteremia. Average antibiotic number (1+ dose per antibiotic) 3.24 (SEM ± 0.16) and total C difficile cases 3 (1.26%). Mortality rate34.45%.Relevant hospitalization characteristics, Covid19 and bacteremia co-infectionsRelevant laboratory parameters for patients with Covid19 and bacteremia co-infectionPatients with Covid19 and bacteremia had high mortality , 53% received immunomodulator therapy, possibly contributing to bacteremia development. With bacteremia increase in WBC and Procalcitonin, not CRP, noted. Most organisms CoNS, likely contaminants, gram positive bacteremias likely from indwelling lines. Only 3 C difficile infections identified. Trends noted in Procalcitonin rise, immunomodulator therapy, and low C difficile infection rates warrant further studies.Post-hospitalization OutcomesAll Authors: No reported disclosures


Staphylococcus aureus (MRSA), but there are limited patient outcomes in the setting of cystic fibrosis pulmonary exacerbation (CFPE). The study objective was to compare the efficacy and safety of TLV to vancomycin (VAN) in CFPE.Telavancin (TLV) is an advanced generation lipoglycopeptide with activity against methicillin-resistant Retrospective cohort conducted from 1/2011-6/2020. Inclusion criteria were: i) age ≥16 years, ii) hospitalized for CFPE with documented signs/symptoms of infection, iii) confirmed or suspected MRSA lower respiratory tract infection, iv) receipt of ≥48 hours of TLV or VAN. The primary outcome was 30-day CFPE-related readmission: infection recurrence, clinical worsening on treatment, or ADE requiring readmission. Secondary outcomes included adverse drug events (ADE) on therapy: acute kidney injury (AKI), rash, thrombocytopenias, cardiac abnormalities. P< 0.001). The median (IQR) time to TLV initiation from admission was 1 (0.8-1.4) days. 13 patients were readmitted within 30-days due to CFPE; 8 (15)% TLV vs. 5 (10%) VAN . Reasons for 30-day CFPE: TLV: 7 infection recurrence, 1 clinical worsening; VAN: 2 clinical worsening, 2 infection recurrence, 1 treatment-related ADE. When accounting for confounders, TLV was not associated with 30-day CFPE-related readmission . Patients who received VAN more commonly experienced an ADE while hospitalized (18%), most notably AKI101 patients were included: 52 (52%) TLV, 49 (49%) VAN. The median (IQR) age was 22 (21-27) years, 50% were women, and 86% were Caucasian. The majority (84%) of patients had some federal health insurance; 19% had private health insurance. 93% of patients used a maintenance cystic fibrosis (CF) medication, and 35% had previous CF-therapy compliance concerns. 62% had a previous positive culture for MRSA; 22 (43%) TLV patients had documented MRSA infection on admission compared to 41 (84%) VAN  ghassan wadi, MD, Cumberland (Grant/Research Support) Michael P. Veve, Pharm.D., Cumberland (Grant/Research Support)Paratek Pharmaceuticals (Research Grant or Support)


Yang LiuBJU Int. 2020 Jul;126(1):168-176.Percutaneous nephrolithotomy (PCNL) is the gold standard surgical treatment for large renal kidney stones >2.0 cm) according to EUA and AUA guidelines , 2. Howe.0 cm accSeveral authors have already reported favorable outcomes of mini-PCNL when compared to RIRS -6. A sim


Cited2 deletion has a minor impact on steady-state hematopoiesis, Cited2-deficient HSCs are severely depleted in young mice and fail to expand upon aging. Moreover, although they home normally to the bone marrow, they fail to reconstitute hematopoiesis upon transplantation. Mechanistically, CITED2 is required for expression of key HSC regulators, including GATA2, MCL-1, and PTEN. Hematopoietic-specific expression of anti-apoptotic MCL-1 partially rescues the Cited2-deficient HSC pool and restores their reconstitution potential. To interrogate the Cited2→Pten pathway in HSCs, we generated Cited2;Pten compound heterozygous mice, which had a decreased number of HSCs that failed to reconstitute the HSC compartment. In addition, CITED2 represses multiple pathways whose elevated activity causes HSC exhaustion. Thus, CITED2 promotes pathways necessary for HSC maintenance and suppresses those detrimental to HSC integrity.Hematopoietic stem cells (HSCs) reside at the apex of the hematopoietic differentiation hierarchy and sustain multilineage hematopoiesis. Here, we show that the transcriptional regulator CITED2 is essential for life-long HSC maintenance. While hematopoietic-specific  •Unperturbed hematopoiesis can be sustained long term while the HSC pool is depleted•CITED2 promotes HSC survival but not quiescence under homeostatic conditions•Mcl1 and Pten expressionCITED2 maintains the HSC pool by controlling  Cited2 deletion causes a progressive HSC loss under steady-state conditions without perturbing normal hematopoiesis. The authors show that CITED2 maintains HSCs by regulating the expression of Mcl1 and Pten. Finally, they indicate that CITED2 promotes multiple pathways necessary for HSC maintenance and suppresses those detrimental to HSC integrity to coordinate HSC function.Kranc, Guitart, and colleagues demonstrate that  Hematop humans) . The strCITED2 (CBP/p300-interacting-transactivator-with-an ED-rich-tail 2) is a transcriptional regulator that co-activates or represses multiple transcription factors, including AP-2 , HIF-1alMx1-Cre-mediated deletion of Cited2 (in which Mx1-Cre is induced by poly(I:C)-stimulated IFN-α production) results in a rapid loss of HSCs via apoptosis and a resultant BM failure  or Trp53 (encoding p53) rescues depletion of Cited2-deficient HSCs. Another study -inducible Mx1-Cre-mediated Cited2 deletion results in loss of HSCs , compromises their reconstitution potential, and leads to a rapid BM failure upon myelotoxic stress. In this study, loss of quiescence, but not increased apoptosis, upon inducible Cited2 deletion is mediated at least in part by HIF-1alpha, as Hif1a deletion partially restores impaired quiescence of HSCs lacking Cited2 and improves their ability to reconstitute the HSC compartment upon transplantation  cells, LSKCD48−CD150+ HSCs, Lin−Sca-1−c-Kit+ (LK) myeloid progenitors, and more-mature Lin– and differentiated Lin+ hematopoietic cell populations, and performed qRT-PCR. Cited2 was expressed in all compartments, with significantly higher expression in the HSC population compared with myeloid progenitors and more mature hematopoietic cell populations (Cited2 in long-term HSCs (LSKCD34−CD135−), MPP1 (LSKCD34+CD135−CD150+CD48−), MPP2 (LSKCD34+CD135−CD150+CD48+), and MPP3 (LSKCD34+CD135−CD150−CD48+) populations, lymphoid-primed multipotent progenitors (LSKCD34+CD135+), which correspond to the MPP4 population, and CMP (LKCD34+FcγRII/IIIlow), GMP (LKCD34+FcγRII/IIIhigh), and MEP (LKCD34−FcγRII/IIIlow) compartments, we analyzed our SMART2-seq single-cell expression data in these populations  mice  analyses of 8- to 12-week-old Cited2CKO mice revealed unaffected WBC counts, with mild anemia and thrombocythemia  mice D, where CKO mice E. Surpricythemia F. Furthelularity G and unalularity H, as wellularity  and 1I.  numbers J. Notabl numbers F, mice lgenitors K. FinallBM cells L and 1M.or cells M. Taken Cited2 deletion on HSCs and primitive progenitor cells. We found that the total number of LSK cells  was not affected in young 8- to 12-week-old Cited2CKO mice , with an increase in MPP2 population and unchanged numbers of the MPP3-4 populations. Thus, despite a select reduction in absolute HSC and MPP1 cell numbers, Cited2CKO mice sustain largely unaffected unperturbed steady-state multilineage hematopoiesis.We next determined the impact of CKO mice A. MarkedCited2 deficiency on long-term HSC maintenance during unperturbed hematopoiesis. We aged mouse cohorts for 52 weeks and found that Cited2 deficiency had no impact on mouse survival (data not shown). Consistent with physiological HSC aging, during which the HSC pool undergoes expansion  and found that they also dramatically failed to reconstitute hematopoiesis  resulted in a partial rescue of the HSC and MPP1 cell pools compared with Cited2CKO mice  is a pro-survival BCL-2 protein family member, whose  failure , thus redeletion . Moreovedeletion . Given tnic mice , which oelements B. IntereCKO mice C. To invent mice D. Signifcl1 mice E and 4F.cl1 mice E and 4F.cipients G. Finallcolonies H, and whol cells I. TherefPten expression was decreased in Cited2-deficient HSCs , Cited2Het, PtenHet, and control mice  did not rescue HSC depletion -inducible ectively . Howevertor Mcl1 , whose hotential . Consistntenance . These dactivity . Indeed,Mx1-Cre deletion of Cited2 results in loss of quiescence of HSCs, a phenotype that is partially mediated by HIF-1alpha  is known to transiently alter HSCs , unlike Vav-iCre, which is constitutively expressed, and as such more accurately allows for gene deletion under steady-state conditions. Thus, it is possible that concurrent poly(I:C) administration and Cited2 deletion in the Mx1-Cre-mediated model may exhibit exacerbated phenotypes not seen in the Vav-iCre model.Poly(I:C)-inducible F-1alpha , 2014. NWhile in this study we focused on functional interrogation of the CITED2→MCL-1 and CITED2→PTEN axes, our work suggests that CITED2 is also likely to control other diverse pathways to coordinate HSC biology. Our analyses indicate that CITED2 represses multiple pathways downstream of c-MYC, E2F, and RUNX1 transcription factors and K-RAS and proinflammatory signaling pathways, whose upregulation has detrimental consequences for HSC integrity . FinallyCited2fl/fl , anti-CD4; biotin conjugated (cat. no. 553649), anti-CD5; biotin conjugated (cat. no. 553019), anti-CD8a; biotin conjugated (cat. no. 553029), anti-CD11b; biotin conjugated (cat. no. 553309), anti-CD45R/B220; biotin conjugated (cat. no. 553086), anti-Ter119; biotin conjugated (cat. no. 553672), anti-Gr-1/Ly-6G/C; biotin conjugated (cat. no. 553125), anti-CD34; FITC conjugated (cat. no. 553733), and streptavidin; BV421 conjugated (cat. no. 563259). BioLegend antibodies used were anti-c-Kit/CD117; APC conjugated (cat. no. 105812), anti-c-Kit/CD117; APC-Cy7 conjugated (cat. no. 105826), anti-Sca-1; APC-Cy7 conjugated (cat. no. 122520), anti-Sca-1; PB conjugated (cat. no. 108125), anti-CD48; PE conjugated (cat. no. 103406), anti-CD150; PE-Cy7 conjugated (cat. no. 115914), anti-CD135; APC conjugated (cat. no. 135310), anti-CD135; PE conjugated (cat. no. 135305), anti-CD16/32; APC-Cy7 conjugated (cat. no. 101328), anti-CD41; APC conjugated (cat. no. 133914), anti-CD105; PE conjugated (cat. no. 120408), anti-CD127; BV421 conjugated (cat. no. 135023), anti-TER-119; FITC conjugated (cat. no. 116206), streptavidin; PerCp conjugated (cat. no. 405213), anti-CD19; APC-Cy7 conjugated (cat. no. 115530), anti-CD45R/B220; APCCy7 conjugated (cat. no. 103224), anti-CD11b; APC conjugated (cat. no. 101211), anti-Gr-1/Ly-6G/C; PE-Cy7 conjugated (cat. no. 108416), anti-CD4; PE conjugated (cat. no. 130310), anti-CD8a; PE conjugated (cat. no. 100708), anti-CD45.1; FITC conjugated (cat. no. 110706), anti-CD45.2; PB conjugated (cat. no. 109820), anti-Ki67; FITC conjugated (cat. no. 652410). Annexin V; FITC conjugated (cat. no. 640906), and 7-AAD (cat. no. 420403) were purchased from BioLegend. DAPI was purchased from Life Technologies (cat. no. D1306).Mice received 30 mg/mL of NAC (Sigma) in drinking water for 4 weeks. The water bottles containing NAC were changed twice a week.6 BM cells stained first for LSK were resuspended in X-Vivo 15 medium (without phenol red) supplemented with 10% FCS, loaded with 5 μM MitoSox red (Invitrogen) for 20 min at 37°C and analyzed using FACS.For detection of mitochondrial super oxide, 3 × 10CFC assays were performed using MethoCult M3434 (STEMCELL Technologies). Colonies were tallied at day 10. For CFC replating, CFC1 cells were washed with IMDM then seeded in M3434.+/CD45.2+ recipient mice was achieved using a split dose of 11 Gy (two doses of 5.5 Gy administered 4 h apart) at an average rate of 0.58 Gy/min using a Cesium 137 GammaCell 40 irradiator. For transplantations 100 HSCs or 2,000 LSK sorted from BM of 8- to 10-week old adult mice mixed with 200,000 support CD45.1+ wild-type BM cells were injected into lethally irradiated CD45.1+/CD45.2+-recipient mice.Lethal irradiation of CD45.1+ BM were injected into CD45.1+ lethally irradiated recipients . After 18 h, recipients were sacrificed and BM CD45.2+ chimerism was analyzed by FACS.LSK cells sorted from CD45.2Actb expression.Gene expression analyses were performed as described previously . DiffereStatistical analyses were performed using GraphPad Prism software. p values were calculated using a Mann-Whitney U test.Cited2CKO and Cited2CTL animals (n = 5 per genotype). On average, 6,200 cells per sample were collected and 53.7 million single-ended 85-bp reads per sample were sequenced. Reads were aligned to the GRCm38 mouse genome using HISAT2 v.2.1.0  were mapped to gene loci using the basic set of ENCODE genomic annotation from Ensembl v.91. Next, proximal promoters were defined as the region from 200 bp upstream to 100 bp downstream of the transcription start site. Proximal promoter coordinates were shuffled within chromosomes using the bedtools shuffle tool with the –chrom flag to generate control DNA regions for motif analysis. Finally, DNA motifs overrepresented in promoters compared with control regions were identified by Homer v.4.10.in vivo experiments, and data analyses and interpretation. L.N.L. and M.B. analyzed gene expression. K.J.C. and S.C. produced VavP-Mcl1 transgenic mice. A.T., J.D., A.V., A.B., C.M., E.G., C.M.-C., C.S., L.A., and J.C. helped with in vivo experiments, FACS, and data analyses. D.O., B.G., and N.P.R. provided significant expertise to this study. K.R.K. and A.V.G. contributed equally to this work.K.R.K., A.V.G., and H.L. designed the experiments and wrote the paper. A.V.G. and H.L. performed The authors declare no competing interests.