FAM107A and p.(Thr220Ala) in SLC26A6 at 3p21 as being predicted to impact on protein function. FAM107A expression was shown to be low or absent in lymphoblastoid cell lines and SLC26A6 expression lower in lymphoblastoid cell lines derived from p.(Thr220Ala) mutation carriers. Expression of FAM107A and SLC26A6 was low or absent in Hodgkin Reed-Sternberg (HRS) cell lines and in HRS cells in Hodgkin lymphoma tissue. No sequence variants were detected in KLHDC8B, a gene previously suggested as a cause of familial cHL linked to 3p21. Our findings provide evidence for candidate gene susceptibility to familial cHL.The heritability of classical Hodgkin lymphoma (cHL) has yet to be fully deciphered. We report a family with five members diagnosed with nodular sclerosis cHL. Genetic analysis of the family provided evidence of linkage at chromosomes 2q35-37, 3p14-22 and 21q22, with logarithm of odds score >2. We excluded the possibility of common genetic variation influencing cHL risk at regions of linkage, by analysing GWAS data from 2,201 cHL cases and 12,460 controls. Whole exome sequencing of affected family members identified the shared missense mutations p.(Arg76Gln) in  Classical Hodgkin lymphoma (cHL) is the commonest lymphoid malignancy of young adults . While cKLHDC8B [Epstein-Barr virus (EBV) infection is causally related to a number of cases , 5, but KLHDC8B .Nodular sclerosis Hodgkin lymphoma (NSHL), the most common histological subtype of cHL in developed countries, is more frequent in young adults and women . With thi.e. logarithm of odds (LOD) score >3.0). Three regions of the genome, however showed evidence of linkage with a LOD score greater than 2.0: 2q35-37 (220-237Mb), 3p14-22 (42-66Mb), 21q22 (42-47Mb) (FAM107A and p.(Thr220Ala) in SLC26A6 mapping to 3p21 as two plausible candidate variants causal for cHL in the family. We confirmed the fidelity of WES for both variants by Sanger sequencing. Finally, we did not identify any rare sequence variants in the previously identified candidate cHL susceptibility gene in this region, KLHDC8B, in any of the affected family members.No region of the genome showed evidence for linkage with cHL in the family at genome-wide significance (42-47Mb) . Linkage2q35-37 2-237Mb, 3SLC26A6 expression was lower in lymphoblastoid cell lines from family members carrying the T220A mutation compared to unrelated healthy individuals , rs115918946 (P = 1.70 × 10–4) and rs2839384 (P = 1.31 × 10–3), which, after adjustment for multiple testing, were not statistically significant . Furthermore, these common genetic variants were not in linkage disequilibrium with the candidate genetic mutations in FAM107A and SLC26A6.To explore the possibility that variants with frequency greater than 1% might contribute to a relationship between 2q35-37, 3p14-22, 21q22 and cHL risk, we analysed directly typed and imputed genotypes in our large case-control series. Across the three regions we examined the relationship for 107,472 SNPs and cHL risk . The strper se, we found suggestive linkage at 3p21, a region previously implicated by Salipante et al. [It is notable that we identified the class II HLA allele (DPB1*0401) as being shared between affected individuals. Although a HLA class II association is well established for NSHL, there is limited evidence to implicate this specific HLA allele. Excluding the possibility of multiplicative interaction with a non-HLA linked allele, the pattern of inheritance of cHL in the family we describe is parsimonious with autosomal inheritance with incomplete penetrance. Predicated on this assumption, we sought to identify a disease locus for cHL in the family by performing a linkage scan. Although not statistically significant e et al. , which iSLC26A6 and FAM107A on chromosome 3p21, as possible candidates for cHL risk. In contrast, we did not identify any mutations in KLHDC8B, which has been previously suggested as a cause of familial cHL [SLC26A6.By performing WES of affected individuals we identified two rare protein-disrupting mutations in lial cHL , and whiSLC26A6 is expressed in many tissues, consistent with its role as an anion transporter [SLC26A6 has so far not been directly implicated in cancer. FAM107A, originally identified in a commonly deleted region on 3p21 in renal cell carcinoma, appears to function as a tumour suppressor [in situ hybridization [SLC26A6 and FAM107A occur in 3.7% (9/241) and 12.9% (31/241) respectively of germinal centre B-cell derived lymphomas [SLC26A6 mRNA expression in LCLs of affected individuals, we have been unable to provide a mechanistic basis by which identified variants in either SLC26A6 or FAM107A contributes to lymphomagenesis.nsporter , 23. SLCppressor –26. Lossppressor , 27–30, ppressor , 32. Howdization . Furtherymphomas . AlthougAlthough WES is a well-recognised strategy to identify disease-causing mutations , 36, it SLC26A6 and FAM107A as possible candidate genes.In summary, our analysis of this family support the existence of a susceptibility locus on chromosome 3p21 for cHL, with exome sequencing suggesting Collection of blood samples and clinical information from subjects was undertaken with informed consent and relevant ethical review board approval , in accordance with the tenets of the Declaration of Helsinki.in situ hybridization (EBER). In all family members, complete remission was attained with first-line standard treatment (i.e. chemotherapy ± radiotherapy). None had a significant medical history or past history of cancers and IV-f was found to have a normal constitutional chromosome karyotype.A family segregating cHL was identified through a female patient (IV-f) diagnosed with NSHL at age 22 under the clinical care of the Department of Haematology at Aberdeen Royal Infirmary, UK Figure . A detaiConstitutional DNA was extracted from EDTA-venous blood or saliva samples using either QiaAMP DNA mini kits  or prep-IT purification  kits and quantified by Quant-IT Picogreen . Family members were genotyped using either Affymetrix 6.0 chips  or Affymetrix 500K (III-a) mapping arrays. CEL intensity files were processed using Affymetrix Power Tools (APT v1.16.1) and PLINK used to harmonise genotypes. Mendelian errors were removed and SNPs with high heterozygosity spaced ∼0.3Mb apart selected using linkdatagen were used for linkage analysis . Non-parTyping of classical HLA alleles was performed using SeCore sequencing  in conjunction with Applied Biosystems 3130XL technology and analysed using uTYPE 6.0 software (Life Technologies) with IMGT as reference (version 3.14.0).i.e. missense, nonsense, frameshift, in-frame insertion/deletions, splice donor/acceptors, and initiator codon variants). Exome Variant Server (NHLBI GO Exome Sequencing Project (ESP) [For WES of germline DNA from III-a, IV-b, IV-f and IV-g was fragmented using a Covaris E Series instrument . Indexed paired-end libraries were prepared using the SureSelect Human All Exon 50Mb  and 2 × 100 bp sequencing performed using Illumina HiSeq2000 technology . Paired end fastq files were extracted using CASAVA software  and aligned to build 37 (hg19) of the human reference genome using Stampy and BWA software , 42. Alict (ESP) , 1000 gect (ESP)  and dbSNct (ESP)  were usect (ESP)  algorithn = 5) patients using primary antibodies to SLC26A6 (Sigma) or FAM107A (Biorbyt) and DAB chromogen (Dako).Immunohistochemistry of SLC26A6 and FAM107A were performed on formalin-fixed, paraffin-embedded material lymph node biopsies from IV-f and sporadic cHL  derived from III-g, IV-f and IV-g and healthy controls (n = 10), HL cells  and other cell lines . RNA was extracted using the RNeasy mini kit  and qRT-PCR performed using a Roche LightCycler 480 thermal cycler. Assays were performed in triplicate with GAPDH as internal control.To evaluate the association between common genetic variation at chromosomes 2q35-37, 3p14-22, 21q22 and cHL we made use of data previously generated on two non-overlapping case-control series of Northern European ancestry, which had been the subject of a previous GWAS . The UK-


TCF3 causes cell death and cell cycle arrest in cHL cell lines. Mechanistically, TCF3 overexpression modulated expression of multiple pro-apoptotic genes including BIK, APAF1, FASLG, BOK, and TNFRSF10A/DR4. We conclude that TCF3 inactivation contributes not only to extinguishing of B cell phenotype but also to cHL oncogenesis.Although Hodgkin and Reed-Sternberg (HRS) cells of classical Hodgkin lymphoma (cHL) derived from germinal or post germinal B cells, they have lost the B cell phenotype in the process of lymphomagenesis. The phenomenon can be at least partially explained by repression of B-cell-specific transcription factors including TCF3, early B-cell factor 1 (EBF1), SPI1/PU.1, and FOXO1, which are down-regulated by genetic and epigenetic mechanisms. The unique phenotype has been suspected to be advantageous for survival of HRS cells. Ectopic expression of some of these transcription factors  indeed impaired survival of cHL cells. Here we show that forced expression of  TCF3 gene. TCF3 is expressed in HRS cells, but its function is antagonized by MSC/ABF1, ID2, and NOTCH1 [TCF3 locus is associated with an increased risk of cHL [BIK, APAF1, FASLG, BOK, and TNFRSF10A/DR4, and p21.Classical Hodgkin lymphoma (cHL) is characterized by the presence of mononucleated Hodgkin cells and multinucleated Reed-Sternberg cells (HRS) surrounded by the overwhelming host cells of “inflammatory infiltrate”. HRS cells are derived from germinal center (GC) B cells which have lost their B cell program in the process of malignant transformation . Multipld NOTCH1 , 5. Mored NOTCH1 –8. The rd NOTCH1 –12. Morek of cHL . In thisbona fide inactivated by ID2 and MSC in cHL, we overexpressed E47, a TCF3 transcription variant, in KM-H2 and SUP-HD1 cell lines using doxycycline (DOX)-inducible vector pRTS containing GFP as a fluorescent marker. DOX treatment activated expression of E47 in both cell lines  [BIK and TCF3 were highly expressed in GC B cells, plasma cells, B-NHLs and nodular lymphocyte predominant Hodgkin's lymphoma (NLPHL). HRS cells of cHL demonstrated lowest expression levels of BIK and TCF3  Figure . The uprn Figure , which iK Figure . Further3 Figure .Finally we investigated whether E47 is able to reactivate known TCF3 targets like FOXO1, ABF1/MSC, POU2F2, CD19, CD79, EBF1, MYC and CDK6. We found that E47 significantly upregulated expression of NOTCH1, ID2, AICDA, and cell cycle regulator CDKN1A Figure . The othTCF3 in cHL cell lines causes apoptosis and cell cycle arrest that is associated with expression of antiproliferative and pro-apoptotic target genes. cHL is characterized by loss of the B-cell phenotype caused by repression of critical regulators of B-cell differentiation. Recently, we and other authors have shown that repression of these transcription factors including FOXO1 [In this study, we have shown that forced expression of ng FOXO1 , EBF1 [8ng FOXO1  has a crng FOXO1 –20. It ing FOXO1 . TherefoMYC, CDK6 and by up-regulation of cell cycling inhibitor CDKN1A/p21, thereby leading to cell cycle arrest [Given that TCF3 is not only an essential regulator in B- and T- lymphocyte development, but also a tumor suppressor in T cell tumors , 22–25, e arrest , 26.BCL2L11 and BIK have been seen [BIK is strongly expressed in GC B cells [BIK expression significantly correlated with TCF3 in normal B cell subtypes and B cell lymphomas. Another interesting finding was the absence of BIK expression in PMBL cell lines. As a distinct subtype of DLBCL, PMBL shares morphological and molecular similarities with cHL. Nevertheless, we were not able to prove contribution of BIK in the E47-induced cell death due to technical reasons. Given that TCF3 activates numerous proapoptotic genes, it is conceivable that tumor-suppressor effect does not depend on a single factor but develops as a “death by a thousand cuts” as it was supposed for IRF4 depletion in multiple myeloma [In regard to molecular mechanisms of TCF3 antitumor effects, in Sézary syndrome (a subtype of T cell lymphoma) derived cells, no significant cell death induction was observed after E47 overexpression, whereas, up-regulation of proapoptotic genes including een seen , 26. In  B cells  and spec B cells , this pr myeloma .BIK expression is regulated by multiple mechanisms. A recent study demonstrated that BIK expression might be a consequence of G1 cell cycle arrest in solid tumor cell lines . BIK wasWe conclude that inactivation of TCF3 contributes to oncogenic program of cHL and might be critical for tumor maintenance.+ B cells were isolated using microbeads (Miltenyi Biotec) as described before [cHL cell lines , Burkitt's lymphoma (BL) cell lines  and other B cell lymphoma cell lines  were cultured in complete RPMI 1640 medium as described earlier , 33. Prid before .www.addgene.org). Human E47 coding sequence was first cut out from pCS2-E47, subsequently the fragment was blunt inserted to EcoRV sites of the pSFI vector and then transferred into the pRTS-1 vector to construct the pRTS-E47 plasmid. Cells were transfected with an Amaxa Nucleofector device  using nucleofection buffer “V”, program Q-07 for SUP-HD1 and U-01 for KM-H2 . Twenty-four hours later, transfected cells were selected with 150 μg/mL Hygromycin B . Efficiency of selection was monitored by FACS analysis of green fluorescent protein (GFP) expression and immunoblotting of the transgene expression 24 h after treatment with 0.5 μg/mL of Doxycycline (DOX).pSFI and pRTS vectors were kindly provided by D. Eick and G. W. Bornkamm  and wereTo construct SF-LV-E47 vector, E47 was amplified from pCDNA3-E47 using primers: 5′-TTAACTCGAGTTAACGCCACCATGAACCAGCCGCAGAGGATG-3 and 5′-GGAGGGAGAGGGGGCTCACATGTGCCCGGCGGG-3; with restriction sites for NotI. Subsequently, E47 was introduced into the NotI restriction site of the lentiviral vector SF-LV-cDNA-EGFP . Lentivwww.genscript.com) and synthesized by biomers.net , sequences 5′ to 3′, sense and antisense, annealing temperature 60°C:The total RNA was isolated using High Pure RNA Isolation Kit , first-strand cDNA with MMLV reverse transcriptase . Templates amplification was done using QuantiTect SYBR Green PCR Kit  on a LightCycler 480 (Roche). Primers were designed with Genscript on-line software . RPL13A was selected for calculations because it was found to be the most reliable. Human apoptosis primer library  was used to identify TCF3/E2A target genes as described before [BIK: AGCTCCTGGAACCCCCGACC and CGC AGGGCCAATGCGTCACT ;RPL13A: d before .Immunoblot was done as described before . Rabbit 6 cells were fixed and stained with 70% cold ethanol and PI. DNA contents were measured by flow cytometry with a FACSCalibur flow cytometer (BD Biosciences). Data were analyzed using ModFit cell cycle analysis software .Cell proliferation was analyzed by cell counting using a Vi-cell XR cell viability analyzer based on the trypan blue dye exclusion method . Viable and dead cells were differentiated and quantified by the cell viability analyzer. Apoptosis was measured by Propidium Iodide (PI) staining and flow cytometry as described . Cell cyAll experiments were independently performed three times. Data were expressed as mean ± standard deviation (SD). Student's t-test was used to determine the significance of difference between two groups, one-way ANOVA was used for multiple comparisons. All statistical analyses were carried out with SPSS13.0 software , p < 0.05 was considered statistically significant. The correlation analysis was calculated using the CORREL function in Microsoft Office Excel (Microsoft Corporation).


Neural precursor cell expressed developmentally downregulated 9 (NEDD9) is a component of the metastatic signatures of melanoma, breast cancer, glioblastoma, lung cancer and head and neck squamous cell carcinoma (HNSCC). Here we tested the efficacy of NEDD9's domains in stimulating matrix metalloproteinase (MMP) secretion and invadopodia formation in cells stably expressing various NEDD9 mutants. Replacement of the 13 YxxP motif substrate domain (SD) tyrosines and the C-terminal Y629 with phenylalanines (F14NEDD9) eliminated tyrosine phosphorylation, MMP9 secretion and loss of invadopodia formation. Mutation of the N-terminal SH3 domain Y12 to glutamic acid (Y12ENEDD9) or phenylalanine (Y12FNEDD9) reduced MMP9 secretion and inhibited invadopodia formation. SH3 domain deletion (∆SH3NEDD9) resulted in the loss of MMP9 secretion and a lack of invadopodia formation. The SH3–SD domain (SSNEDD9) construct exhibited tyrosine phosphorylation and stimulated MMP9 secretion, as did ∆CTNEDD9 which lacked the C-terminus . E13NEDD9 expression blocked MMP9 secretion and invadopodia formation. MICAL1 (molecule interacting with Cas-L1) silencing with a short hairpin RNA reduced MMP9 secretion, vimentin and E-cadherin levels while increasing N-cadherin and Rab6 levels, consistent with reduced invasive behavior. These findings indicate that NEDD9 SD phosphorylation and SH3 domain interactions are necessary for increasing MMP9 secretion and invadopodia formation. Invasion is a property of cancer cells, providing a mechanism by which they exit the primary tumor, traverse the stroma and access the vasculature/lymphatics for distal metastasis. Accordingly, invasive cancer cells must be capable of assembling invadosome structures termed invadopodia that represent sites of focal matrix metalloproteinase (MMP) secretion . Invadopteolysis . In additeolysis .In humans the MMPs represent a large family of at least 24 zinc-dependent endopeptidases that is divided into 4 subgroups based on domain composition . The gelInvasion and metastatic disease represent the underlying cause of morbidity and mortality for most solid tumors , 10. HowWhile invadopodia and FAs perform different functions, they have a number of proteins in common, including paxillin, cortactin and focal adhesion kinase (FAK) . FAs havNEDD9 has a modular domain structure, homologous to that of p130Cas/BCAR1, comprised of an N-terminal SH3 domain (residues 3–65), a substrate domain , a serine-rich region  and a C-terminal focal adhesion (FA) targeting (FAT) domain . The elevated phosphorylation of Y12FNEDD9 is similar to what was observed with Y12Fp130Cas , was reported to enhance cell migration with substitution to Y189D being inhibitory . This diet al., showed that Src is required for NEDD9 signaling to mesenchymal over amoeboid movement [Substituting glutamic acid or phenylalanine at position Y12 within the SH3 domain was based on a report where these substitutions in p130Cas decreased or increased tyrosine phosphorylation, respectively, and in which Y12Fp130Cas expression caused increased FA formation . Increasmovement  and Bradmovement  reportedY12FNEDD9 and Y12ENEDD9 each exhibited enhanced SD tyrosine phosphorylation, decreased MMP9 and increased MMP2 secretion. These findings suggest that SD tyrosine phosphorylation is not sufficient for MMP9 secretion and invadopodia formation. The lack of MMP9 secretion observed may be due to Y12FNEDD9 being preferentially localized to FAs. Alternatively, SH3 domain and SD interactions may both be required for MMP9 secretion and invadopodia formation. This may reflect Src binding to the SH3 domain in WTNEDD9 expressing cells. These findings support the requirement for MMP9 secretion in order for cells to form invadopodia. Our results are in accord with the known differential regulation of MMP2/9 , 40–43 aDrosophila [Based on the notion that invadopodia are sites of focal MMP9 secretion, we examined a role for MICAL1 involvement downstream of NEDD9. MICAL1 was originally isolated as a NEDD9 binding partner . The MICosophila , the disosophila  and Rab osophila . MICAL1 osophila . Reducedosophila . The decosophila .Elevated expression of MMP2 and MMP9 is associated with higher rates of local recurrence and regional/distant metastasis in HNSCC of the tongue with MMP9 having the highest specificity . MMP9 isDMEM and mitomycin C were from Sigma . BCA reagent was obtained from Pierce . The NEDD9 construct was generously provided by Dr. Erica Golemis (Fox Chase Cancer Center). All NEDD9 plasmids contained an N-terminal EGFP. F13, F14, Y12E, Y12F, SS, SH3and ∆SH3 were generated using WTNEDD9 and confirmed by DNA sequencing; ∆CTNEDD9 and BCAR3 were from Dr. K. O’Neill, Australia. All other chemicals were of reagent grade or higher.Monoclonal 4G10 Anti-phosphotyrosine (pY) (1:1000 for WB) and anti-actin C4  antibodies were obtained from Millipore . Polyclonal anti-Rab1 FL205 (1:500 for WB and 1:250 for IF), anti-Rab6 C19 (1:500 for WB and 1:250 for IF), anti-E-Cadherin H108 (1:500 for WB) antibodies and monoclonal NEDD9 (2G9) (1:250 for PLA and IF and 1:250 for IP) and anti-vimentin RV202  antibodies were from Santa Cruz Biotech . Polyclonal anti-MICAL1 antibody  was obtained from Proteintech . Polyclonal anti-NEDD9 C-terminal (1:500 for IF and PLA) antibody was from Sigma-Aldrich . Polyclonal N-Cadherin D4R1Hxp (1:1000 for WB) antibody and monoclonal anti-Scr L4A1 (1:1000 for WB) were obtained from Cell Signaling Technology . Polyclonal anti-BCAR3 (1:2000 for WB and 1:200 for PLA) was from Bethyl Laboratories . Polyclonal anti-GFP (1:5000 for WB) was generously provided by Dr. Scott T. Eblen . Monoclonal anti-GAPDH 6C5  was obtained from Abcam . Polyclonal anti-GFP (1:500 for IP) was from Genetex . HRP-conjugated goat-anti-mouse (1:5000 for WB) and goat-anti-rabbit (1:1000 for WB) secondary antibodies were obtained from Jackson ImmunoResearch Laboratories . HRP-conjugated donkey-anti-chicken (1:7500 for WB) secondary antibody was obtained from Thermo Fisher Scientific .® and sorted. Mission® shRNAs in the pLKO.1-Puro were packaged into lentivral particles in HEK293T cells followed by transduction into cell lines as described by the manufacturer. For plasmid DNA, cell suspensions were transfected with Nanojuice® (EMD Millipore) according to the manufacturer’s protocol.SCC9 and SCC25 cells  were maintained as described elsewhere , 57. CelStandard immunoblot analysis of whole cell lysates was carried out as previously described .3 cells/well for 1 h. SFM in the upper and lower chambers was exchanged for fresh SFM containing the treatment indicated and cells incubated for 24 h. Each filter was rinsed with PBS and stained with a 1:10,000 dilution of Hoechst dye in PBS for 10 min. The top portion of each filter was swabbed with a Q-tip and washed three times with PBS. Cells on the filter bottoms were imaged with a DAPI filter and nuclei were counted using Cell Profiler v1.0.4942 [Serum-starved cells were plated in the top chamber of matrigel-coated transwell filters in 24 well plates at a density of 30 × 101.0.4942 .Secreted MMPs in conditioned medium were affinity adsorbed with gelatin-Sepharose as previously detailed , 60. SDSCoverslips (#1) were coated with 80 µl of warmed gelatin (comprised of fluorescently labeled:unlabeled gelatin or fibronectin at a 1:8 ratio) as previously described . Coated Cells seeded on coverslips were fixed in 4% paraformaldehyde, permeabilized with 0.1% Triton X-100 and blocked with 1% BSA in PBS for at least 30 min. 100 µl of primary antibody diluted in 1% BSA and 0.1% Triton X-100 in PBS was added for 1 h followed by washing and secondary antibody (1:200) addition for 1 h. Coverslips were rinsed with PBS, inverted onto a glass slide with anti-bleaching sealant and sealed with fingernail polish. Labeled cells were imaged on an Olympus FluoView FV10i laser scanning confocal microscope with 405, 473, 559 and 635-nm lasers, in the xyz and xzy planes or with a Leica TCS SP2 AOBS laser scanning confocal microscope with 458, 477, 488, 514, 543 and 633-nm lasers. Images were prepared for publication using Olympus FluoView, Leica Imaging and ImageJ Fiji software.T-test.Summary statistics for all continuous variables are presented as means and standard deviations. Categorical data are summarized as frequencies and percentages. Differences in baseline characteristics between the local disease group and advanced disease group were analyzed using the Student’s


DNA Damage Response (DDR) and DNA repair pathways are emerging as potent, ubiquitous suppressors of innate immune signaling in human cells. Here, we show that human cells surviving depletion of the Single Strand Break (SSB) repair protein PARP1 undergo p21-dependent senescence or cell cycle checkpoint activation in the context of activation of innate immune signaling, or viral mimicry. Specifically, we observe induction of a large number of interferon-stimulated genes (ISGs) and multiple pattern recognition receptors  and increased nuclear IRF3 staining. Mechanistically, depletion of the double-stranded RNA (dsRNA) helicase RIG-I or its downstream effector MAVS specifically rescues ISG induction in PARP1-depleted cells, suggesting that the RIG-I/MAVS pathway is required for sustained ISG expression in this context. Experiments with conditioned media or a neutralizing antibody to the α/β-IFN receptor revealed that persistent ISG expression additionally requires an autocrine/paracrine loop. Finally, loss of PARP1 and radiation-induced DNA damage strongly synergize in the induction of p21 and ISGs. Overall, these findings increase our understanding of how PARP1 may suppress deleterious phenotypes associated to aging, inflammation and cancer in humans. In response to viral infection, human cells activate an interferon (IFN)-dependent antiviral program . InitialType I IFN signaling can also be activated by cytoplasmic nucleic acids in the absence of viral infection . In this context, DNA damaging agents are well-known to induce IFNs via multiple mechanisms (reviewed in ). For exIn addition to exogenous treatments, intrinsic defects in DNA double-strand break (DSB) repair, commonly found in cancer cells and in normal cells with aging, are sufficient to promote innate immune signaling. For example, the DNA/cGAS/STING pathway is activated in cells deficient for the ATM kinase . In addiPARP1, a ubiquitous SSB repair factor, is the founding member of a family of proteins with a carboxi-terminal PARP domain . PARP1 bTo investigate how PARP1 maintains homeostasis in human cells, we have analyzed here the phenotypes of clonal populations emerging upon PARP1 gene inactivation via CRISPR/Cas9 editing of the PARP1 locus. We find that depletion of PARP1 triggers type I IFN signaling and identify the dsRNA sensor RIG-I and the type I IFN receptor as key elements in the maintenance of this IFN-dependent transcriptional program.HCT116 and HEK293T cells were grown in 10%FBS/DMEM supplemented with penicillin/streptomycin in a humidified incubator at 37°C. Both lines were authenticated using Short Tandem Repeat (STR) Profiling at the Johns Hopkins Genetics Resources Core Facility using the GenePrint 10 kit (Promega).D10A nickase) were obtained from Addgene [CACCGCCACCTCAACGTCAGGGTGC; R: AAACGCACCCTGACGTTGAGGTGGC; exon 2 guide B: F: CACCGTGGGTTCTCTGAGCTTCGGT; R: AAACACCGAAGCTCAGAGAACCCAC. For cloning of annealed oligonucleotides into PX459 or PX462, a simplified digestion/ligation reaction was performed. A 20 μL reaction containing 2 μL of annealed oligos (0.5 μM), 100 ng of vector, 1μL of FastDigest BbsI (Thermo Scientific) and 1μL of T4 ligase (New England Biolabs) was incubated in 1X FastDigest buffer at 37°C for 2 hours in a waterbath and used for bacterial transformation. To confirm the inserts, colony miniprep DNA was sequenced using a sequencing forward primer 5’-TGTAAACACAAAGATATTAG-3’. Plasmids were transfected into HEK293T cells using Fugene and HCT116 cells with Lipofectamine 3000 transfection reagents. For experiments aimed at testing the efficiency of editing, transfected cells were selected in puromycin  for 3–4 days and harvested for analyses by T7 assays and sequencing, as described below. For experiments aimed at generating KO lines, cells were subjected to sequential rounds of transfection/selection, cells were kept in conditions of exponential growth after the first selection and retransfected when puromycin sensitivity was restored. Cells were single cell subcloned in 96-well plates and expanded to 6-well plates for clone analysis.Vectors pSpCas9(BB)-2A-Puro  and pSpCas9n(BB)-2A-Puro  to allow for annealing of mismatched DNA molecules. After addition of 1 μL of T7 endonuclease , samples were incubated at 37°C for 1 hour, resolved in a 2% agarose gel and photograph using a GelDoc apparatus (BioRad).The targeted regions were amplified from gDNA as above and cloned into TOPO-TA (ThermoFisher Scientific) following manufacturer instructions. Colony miniprep DNA was sequenced at the Johns Hopkins Genetics Core Facility and aligned to the consensus PARP1 sequence.5 cells in 10-cm dishes and, after 10 days, cells were counted using a Celometer Auto T4 cell counter. For HCT116 cells, 7.5 X 104 cells were plated on each well of 6 well plates in triplicate and counted after each day for 2–3 days.For HEK293T cells, we seeded 10We seeded 200 cells in each well of 6-well plates. After 15 days, colonies were stained with crystal violet and counted. Representative images were taken using a digital camera.EV and HCT116PARP1-/- cells (1x107) were mixed with Growth Factor Reduced Matrigel  1:1 and injected into the flanks of NSG mice. Tumor diameters were measured using a caliper and tumor volume was calculated using the formula (L*W2)/2.HCT116To quantify cell cycle distribution, exponentially growing cells were fixed in cold 70% ethanol, permeabilized in Triton-X, digested with RNAse A and stained with propidium ioidide (PI). All data was acquired using a FACSCalibur and analyzed with FlowJo software.Cells were fixed and incubated in β–gal using a commercial kit , following the manufacturer’s instructions. For quantification, images were taken using an EVOS microscope and we quantified n = cells per field; n = 2 fields per well in triplicate wells of a 6-well plate.Total RNAs were isolated from cells in culture using RNAeasy mini kit and on column DNase I treatment following manufacturers instruction . One microgram of total RNA from each sample were submitted to the Johns Hopkins University Deep Sequencing and Microarray Core for sequencing and analyses. Briefly, libraries are prepared using Illumina TruSeq stranded total RNA sample preparation kit following the manufacturer's recommended procedure. All six samples are pooled together and sequenced on Illumina NextSeq using a 300cycle High Output reagent kit for paired end 100bp sequencing. The illumina NextSeq RTA software version 2.4.11 was used for base calling and illumina bcl2fastq software version 2.17.1.14 was used to generate fastq files and trimming adapter sequences. RNAseq data is aligned to human reference genome hg19 using tophat 2 (version 2.0.14) and differential expression detected using cufflink software (version 2.2.1). This final differentially expressed gene table with their respective absolute expression values were used to run Ingenuity Pathway Analyses , Gene Set Enrichemnt assay , Gene Ontology on the Panther Gene ontology platform, and CufTotal RNA was reverse-transcribed into cDNA using SuperScript® III Reverse Transcriptase System  and oligo(dT)20 primers. All qPCR experiments were performed using ddCt method and PowerUp SYBR Green Master Mix  on a CFX384 BioRad Real-Time PCR System . 18S was used as the endogenous control. All primers used in this study are listed in the Cells were fixed in 4% formaldehyde for 5 min followed by cold methanol 10 min and stained with a rabbit polyclonal antibody to IRF3 . After incubation with a secondary antibody , cells were mounted in Vectashield with DAPI. Images were acquired using a Zeiss Axioplan Imager Z.1 microscope equipped with a Zeiss AxioCam and an HXP120 mercury lamp (Jena GbH) and analyzed using dedicated software (Zeiss Axiovision Rel4.6). For comparison, we recorded five random fields using a 60X objective within each sample.Cells were resuspended in RIPA buffer supplemented with PMSF, protease inhibitors and the phosphatase inhibitors sodium fluoride, sodium orthovanadate and β-glycerophosphate. Fifty μg of protein were resolved via SDS-PAGE, transferred to PVDF membranes and blotted with antibodies to the following proteins: PARP1 ; p53 ; phospho-p53 (Ser15) ; p21 ; PAR , γ-H2AX , phospho-KAP1 (Ser824) ; phospho-CHK2 ; STING ; MDA-5 ; MAVS ; RIG-I ; TLR3 . Secondary antibodies were HRP-linked anti-mouse  and HRP-linked anti-rabbit IgG . To control for loading, blots were hybridized with an HRP-conjugated antibody to GAPDH .5 per 6-cm dish) were transfected with siRNAs  following the manufacturer’s protocol. Cells were harvested for analysis 96 hrs post transfection. All siRNAs were purchased as SMARTpools from Dharmacon and used at 100 nM. Specifically, we used products L-012511-00-0005 (DDX58/RIG-I); L-013041-00-0005 (IFIH1/MDA-5); L-024237-00-0005 (MAVS); L-024333-02-0005 (TMEM173/STING) and L-007745-00-0005 (TLR3). As a control, we transfected cells with a pool of nontargeting siRNAs .Cells (2x10EV and HEK293TEV cells (4x105 cells) were seeded in 6-cm dishes with conditioned media from either EV cells or PARP1 KO clones for each line. Conditioned media was replaced once after 2 days and cells were harvested and counted at day 5.HCT1164 cells per well in a 6-well plate) were incubated with anti-human interferon α/β receptor chain 2 (IFNR) antibody, clone MMHAR-2  or with an isotype control  and counted or harvested for RNA after 72 hours.Cells , Xstrahl Ltd., UK, operating at a dose rate of 3.93 Gy/min.5 cells per 6-cm dish) were incubated with all three compounds or vehicle for 72 hours prior to harvesting for RNA.Methylmethane sulfonate (MMS) was purchased from Sigma (#129925). Olaparib/AZD2281 was purchased from Selleckchem (#S1060). For experiments aimed at reverse transcriptase inhibition, didanosine (S1702), neviparine (S1742) and zidovudine (S2579) were all purchased from Selleckchem. Cells (2x105 per 6-cm dish) were transfected with pEGFP-hPARP1-C1 plasmid using Lipofectamine 3000  and harvested 72 hours post transfection for cell counts and RNA.Cells .3 PNA probe (Applied Biosystems), washed and mounted in Vectashield with DAPI . Images were obtained using a Zeiss Axioplan Imager Z.1 microscope equipped with a Zeiss AxioCam and an HXP120 mercury lamp (Jena GmbH) and dedicated software (Zeiss Axiovision Rel 4.6). For quantitative analysis of telomere length on metaphases, we employed TFL-Telo software (kind gift of Dr. Peter Lansdorp). We analyzed 10 metaphases per sample.Cells were incubated in 0.1 μg/mL colcemid  for 4 hr, swollen in 0.45% KCl for 30 min at 37°C and fixed in methanol/acetic acid (3/1). Metaphases were hybridized with a telomere peptic nucleic acid (PNA) probe as described . Brieflyt-test was performed using Excel software to calculate the statistical significance of the difference in mean values and the P value. A P value of <0.05 was considered statistically significant. *P<0.05; **P<0.01; ***P<0.001.Data is represented as the mean and standard deviation (s.d.) of at least 3 replicates within each experiment. For two group comparisons, an unpaired two-tailed Student’s D10A (“double nicking” [D10A did not result in measurable editing (To “knock out” (KO) PARP1 in human cells, we introduced DSBs at PARP1 exon 2 using a pair of gRNAs coupled to Cas9nicking” ). When t editing . These d editing .PARP1-/- clones, C2 and C4, for additional studies. Sequencing of the target region revealed deletions and indels predicted to result in truncations and null alleles and confirmed their clonal origin from independent events  PARP1 KO clones  or lower than (clone C5) the endogenous level  or canonical NonHomologous End Joining (NHEJ). To characterize DNA repair in HCT116PARP1-/- cells, we assessed the kinetics of cell cycle progression and DDR activation in response to IR, an agent that introduces SSBs and, to a lesser extent, DSBs  and phospho-CHK2 (Thr68) after IR  or RNA  during viral mimicry . These fEV cells . MoreoveEV cells , suggestEV cells , a main PARP1-/- survivors. Although GSEA analysis also revealed enrichment for “Interferon Alpha Response” in HEK293T cells  or individually with Cas9 (“nuclease”) in HEK293T cells. After puromycin selection, the target region was amplified from genomic DNA and editing was measured via the T7 assay. Black arrow points to the unedited (wild-type) band. Lower molecular bands of the expected size were observed. (C) Editing of the target region was confirmed by Sanger sequencing of the target region after TOPO-TA cloning of PCR products. The consensus sequence is shown on top. (D) Expression of either gRNA A or B with Cas9D10A did not result in genome modification in the T7 assay.(A) Sequence of gRNAs A and B binding to sequences within exon 2 of PARP1, downstream of the ATG. (B) To quantify the efficiency of genome editing, both gRNAs A and B were expressed together with Cas9(PDF)Click here for additional data file.S2 FigD10A in HCT-116 cells. After puromycin selection, the efficiency of “double nicking” was measured via the T7 assay. Black arrow, unmodified band; red arrows, modified products. (B) After single cell subcloning and immunoblotting for PARP1, clones C2 and C4 were selected for further analysis. To ensure clonality, gDNA was amplified and PCR products were cloned into TOPO-TA and sequenced. The modified alleles are expected to yield a truncated mRNA, consistent with lack of protein expression. The consensus sequence is shown on top.(A) gRNAs A and B were expressed together with Cas9(PDF)Click here for additional data file.S3 FigD10A but no gRNAs. (B) Cell proliferation for 6 KO clones and control EV cells. 105 cells were seeded in 150 mm plates and counted at day 10. (C-D) Cloning efficiency of KO clones C5 and C9 relative to control EV cells. Bars in (C) represent the average and standard deviation of 3 plates, normalized to EV. Representative examples are shown in (D). (E-F) Xenograft assay of PARP1 KO clone C5 relative to control EV cells. Cells were injected in the flanks of NGS mice and tumor volume measured at the indicated timepoints. Graphs in (E) represent the average and standard deviation of 5 tumors per line. Representative tumors at day 20 are shown in (F). (G) Example of senescent cells  in PARP1-deficient cultures (clone C5). (H-I) Cell cycle analysis of six KO clones and control EV cells. The percentage of cells with 4N DNA content in shown. Bars in (H) represent the average and standard deviation of 3 independent experiments. Representative examples are shown in (I). (J) Analysis of RNA-Seq data for members of the CDKN2 and CDKN1 families. (K) Extracts from PARP1-deficient cells (clones C5 and C9) and control EV cells were probed with antibodies to p21, p53 and, as a loading control, GAPDH.(A) After targeting of PARP1 exon 2 using the “double nickase” approach, single cell-derived subclones were expanded and extracts immunoblotted with an antibody to PARP1. Knock out (KO) clones are indicated by red asterisks. EV, extracts from cells transfected with an “empty vector” expressing Cas9(PDF)Click here for additional data file.S4 FigEV cells (lane 1). GAPDH, loading control. (B) To confirm that the reconstituted PARP1 protein was active, extracts from reconstituted cells were probed with an antibody to PAR in baseline conditions or 15 minutes after exposure to IR (to induce PARylation). GAPDH, loading control. (C-D) PARP1 reconstitution partially rescues resistance to the PARP inhibitor olaparib in PARP1-deficient cells. Cells counts after exposure to 5 μM olaparib or vehicle (DMSO) for 48 hours revealed that PARP1-deficient clones C5 and C9 are olaparib-resistant (C). Upon PARP1 re-expression, sensitivity to olaparib was partially restored (D). Bars represent the average and standard deviation of triplicates. Data is representative of two independent experiments. (E-F) PARP1 reconstitution did not significantly rescue defects in proliferation in PARP1-deficient cells. A proliferation assay of PARP1-deficient and reconstituted cells is shown in (E). Bars represent the average and standard deviation of triplicates. The experiment is representative of two independent experiments. Cell cycle analysis of PARP1-deficient C9 cells and PARP1-reconstituted C9 cells is shown in (F). The percentage of cells with 4N DNA content is indicated.(A) After infection with a lentiviral vector containing the PARP1 cDNA or a control vector lacking cDNA insert, PARP1 expression was quantified by immunoblotting. The level in reconstituted cells was compared to the endogenous levels in HCT116(PDF)Click here for additional data file.S5 FigEV cells). GAPDH, loading control. (C-D) PARP1 reconstitution partially rescues resistance to the PARPi olaparib in PARP1-deficient cells. Control HCT116EV or PARP1-deficient clones C2 and C4 were treated with 5 μM olaparib or vehicle (DMSO) for 48 hours and cells were counted (C). To assess the effect of reconstitution on olaparib sensitivity, reconstituted cells were treated with 5 μM olaparib 3 days after transfection and counted after 48 hours of continuous treatment (D). For all graphs, bars represent the average and standard deviation of triplicates or quadruplicates. Data is representative of two independent experiments. (E) Cell counts of null and PARP1-reconstituted HCT116PARP1-/- cells, clones C2 and C4, at day 7 after transfection.(A-B) HCT116 cells were transfected with a plasmid expressing GFP-PARP1. A representative image of the culture 48 hours after transfection is shown in (A). To quantify PARP1 expression in reconstituted cells, extracts of PARP1-reconstituted and parental PARP1 null cells (clones C2 and C4) were hybridized with an antibody to PARP1 (B). The endogenous and the higher molecular weight GFP-PARP1 species are indicated. For comparison, the endogenous level of PARP1 is shown in lane 1 (HCT116(PDF)Click here for additional data file.S6 FigPARP1-/- cells (clones C2 and C4) and control HCT116EV cells were incubated in colcemid, fixed and metaphase spreads were hybridized with a PNA probe that binds to telomere sequences . DNA was counterstained with DAPI (blue). Representative metaphases are shown.Exponentially growing HCT116(PDF)Click here for additional data file.S7 FigPARP1-/- cells (clones C2 and C4) and control PARP1-proficient HCT116EV cells were treated with 0.01% MMS for 2 hours and cells were counted after 48 hours. Bars represent the average and standard deviation of triplicate plates per experiment, pooled from 2 independent experiments. (B) HCT116PARP1-/- cells (clones C2 and C4) and control PARP1-proficient HCT116EV cells were treated with 0.05% MMS for 2 hours cells were counted after 48 hours. Bars represent the average and standard deviation of triplicate plates. Data is representative of 3 independent experiments.(A) HCT116(PDF)Click here for additional data file.S8 FigPARP1-/- cells (clones C5 and C9) and control, PARP1-proficient HEK293TEV cells at the indicated timepoints after exposure to IR (5 Gy). The percentage of cells with 2N and 4N DNA content is indicated. (B) HEK293TPARP1-/- cells (clones C5 and C9) and control HEK293TEV cells were exposed to IR (5 Gy) and extracts were harvested at the indicated timepoints after IR and probed with antibodies to gamma-H2AX, phospho-KAP1 (Ser824) and phospho-CHK2 (Thr68).(A) Cell cycle distribution of HEK293T(PDF)Click here for additional data file.S9 Figvs. p value (y axis). Data from 2 independent PARP1 null clones per line was compared to the empty vector (EV) control line. Red, induced mRNAs; blue, repressed mRNAs. Blue arrow points to PARP1 mRNA. (B) Scatter plot analysis of mRNAs differentially expressed in HCT116 PARP1-/- cells vs. HEK293TPARP1-/- cells.(A) Volcano plots of fold change (x axis) (PDF)Click here for additional data file.S10 FigPARP1-/- cells (clones C2 and C4) relative to HCT116EV cells were prominently enriched for Molecular Function: “binding” (level 1); “protein binding” (level 2” and “receptor binding” (level 3). (B) Enrichment for the same hierarchy was observed in HEK293TPARP1-/- cells (clones C5 and C9) relative to HEK293TEV cells.(A) mRNAs induced in HCT116(PDF)Click here for additional data file.S11 FigEV HEK293TPARP1-/- (clones C5 and C9).(A-B) RNA-Seq data was analyzed using GSEA. The enrichment plot for “Interferon Alpha Response” genes is shown in (A). A heatmap showing differential expression for individual genes in this category is shown in (B). (C) Quantification of mRNA for 12 interferon-inducible genes (ISGs) in HEK293T(PDF)Click here for additional data file.S12 FigEV cells was normalized to the expression of the same mRNA for HCT116 EV cells. Values below 1 indicate higher expression in HCT116EV cells; values higher than 1 indicate higher expression in HEK293TEV cells.ISG mRNA was quantified by RT-PCR in parallel for the two lines and normalized to ribosomal RNA18S. The expression of each mRNA in HEK293T(PDF)Click here for additional data file.S13 FigEV cells and HEK293PARP1-/- cells (clones C5 and C9) were hybridized with antibodies to MDA5 (A), RIG-I (A), MAVS (A), TLR3 (B) and STING (B). Extracts from HCT116EV and HCT116PARP1-/- cells (clones C2 and C4) were analyzed in parallel for direct comparison. GAPDH, loading control.Extracts from control HEK293T(PDF)Click here for additional data file.S14 FigEV cells (= 1). Bars represent the average and standard deviation of quadruplicates. Data is representative of two independent experiments.Cells were transfected with siRNA pools for each factor (100 nM) and mRNA expression was quantified by q-RT-PCR 4 days after transfection. All values are normalized to the expression in untreated HCT116(PDF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(PDF)Click here for additional data file.S4 Table(PDF)Click here for additional data file.S5 Table(PDF)Click here for additional data file.S6 Table(PDF)Click here for additional data file.S7 Table(PDF)Click here for additional data file.


FH) cells is a possible cause of impaired germinal centre (GC) and IgG antibody responses in individuals with human immunodeficiency virus-1 (HIV-1) infection and might contribute to decreased magnitude and isotype diversification of IgG antibodies to pneumococcal polysaccharides (PcPs). We examined the production of IgG1 and IgG2 antibodies to PcPs 4, 6B, 9V and 14 by enumerating antibody secreting cells (ASCs) at day (D) 7 and determining fold-increase in serum antibody levels at D28 after vaccination with unconjugated PcPs in HIV seronegative subjects (n = 20) and in HIV patients who were receiving antiretroviral therapy (ART) (n = 28) or who were ART-naive (n = 11) and determined their association with ICOS+ and ICOS- circulating memory TFH (cmTFH) cells (CD4+CD45RA-CD27+CXCR5+PD-1+) and short lived plasmablasts (SPBs) at D7, and with PcP-specific and total IgM+ and IgG+ memory B cells at D0. In HIV seronegative subjects, production of IgG1+ and IgG2+ ASCs was consistently associated with the frequency of ICOS+ cmTFH cells but not ICOS- cmTFH cells or memory B cells. In contrast, post-vaccination ASCs in HIV patients, regardless of ART status, were lower than in HIV seronegative subjects and not associated with ICOS+ cmTFH cells, the expansion of which was absent (ART-naive patients) or much lower than in HIV seronegative subjects (ART-treated patients). Production of SPBs was also lower in ART-naive patients. Fold-increase in IgG2 antibodies at D28 also correlated with ICOS+ cmTFH cells at D7 in HIV seronegative subjects but not in HIV patients. These novel findings provide evidence that ICOS+ cmTFH cells contribute to the regulation of PcP-specific IgG antibody responses, including isotype diversification, and that TFH cell dysfunction may be a cause of impaired PcP-specific IgG antibody responses and increased susceptibility to pneumococcal disease in HIV patients.Dysfunction of T follicular-helper (T Rates of invasive pneumococcal infection are increased by up to 100-fold in individuals with chronic human immunodeficiency virus-1 (HIV-1) infection and not fully corrected by antiretroviral therapy (ART) and vaccination with pneumococcal polysaccharides (PcPs) . Decreas2 occurring downstream of γ3 and γ1  supplemented with 1.0μg/mL IL-2  and 2.5μg/mL R848  as described previously [2. The preparation of ELISpot plates and cell viability was done as described above. The cultured PBMC were washed thoroughly, plated in duplicate onto the ELISpot plates at 5 x104 cells per well and incubated for 16–24 hours at 37°C, 5% CO2. Plates were then washed with PBST followed by PBS. Memory B cells specific for PcP 4, 6B, 9V and 14 bound to the plate were detected with alkaline phosphatase-conjugated anti-human IgG and IgM antibody  for 4 hours at room temperature. Plates were washed and developed as described above. Data are presented as the proportion of IgG+ or IgM+ memory B cells per 5x104 PBMC with background values subtracted.IgMeviously . Unstimu+ and IgG2+ ASCs between groups at day 7 were assessed using the non-parametric Mann-Whitney test. Correlations between variables were evaluated by the non-parametric Spearman’s rank correlation test. Differences in IgG1+ and IgG2+ ASC responses between and within groups over time were examined using repeated measures negative binomial regression due to the count nature of the data and the presence of over dispersion. IgG1+ and IgG2+ ASC proportions were predominantly 0 at D0 and D28 preventing the repeated measures negative binomial analysis from producing a solution. Hence, non-parametric tests  were performed. To generate p values for plasmablasts, a log transformation was performed and analysed using linear mixed models. To evaluate proportions of ICOS+ and ICOS- cmTFH cells, a Wilcoxon signed rank test for within group and Kruskal Wallis for between groups was performed.Sample characteristics are summarised using medians, ranges and proportions as appropriate. Differences in baseline characteristics between groups were tested using Mann Whitney test or Fisher’s exact test as appropriate. Differences in IgG1+ and IgG2+ ASCs after vaccination and a priori selected independent variables, including pre-vaccination CD4+ T cell count, proportions of IgM+, IgG+ PcP-specific and total memory B cells, and post-vaccination ICOS+ and ICOS- cmTFH cells, was investigated using a negative binomial regression model. This analysis was performed for each combination of the independent variable and the ASC outcomes. The IRR obtained provided an estimate of the size of the change in the outcome for a one-unit increase in the independent variable. The size of the IRR indicates the strength of the association. Differences between HIV patients and HIV seronegative subjects in the relationship between IgG1+ and IgG2+ ASCs and the independent variable were tested using an interaction term. p values for the coefficients for each patient group were obtained using model based contrasts. Statistical analyses were performed using Prism Version 5.04 software (GraphPad) and Stata 12 . For all tests, p<0.05 was considered significant. Adjustments for multiple comparisons were not made due to the exploratory nature of the study. No formal power analyses were performed due to the pilot nature of the study.The association between PcP-specific IgG1S1 Fig5 PBMC with background values subtracted. The horizontal lines indicate median values. (A) ART-treated HIV patients (B) ART-naive HIV patients (C) HIV seronegative subjects to PcP 6B, (D) ART-treated HIV patients (E) ART-naive HIV patients (F) HIV seronegative subjects to PcP 9V and (G) ART-treated HIV patients (H) ART-naive HIV patients (I) HIV seronegative subjects to PcP 14. Repeated measures negative binomial regression analysis and non-parametric tests for IgG1+ and IgG2+ ASC counts at D0 and D28. n.s., not significant and p<0.05 considered significant. *p value could not be calculated because there was no variance between day 0 and day 28.ASC responses were measured by ELISpot in unstimulated PBMC before (D0), one week (D7) and four weeks (D28) after vaccination with PcPs. Data are presented as ASC/2x10(PDF)Click here for additional data file.S2 Fig-CD27++CD38++. Plots shown are from a HIV seronegative subject D0 (top), D7 (middle) and D28 (bottom) post-vaccination.Representative plot showing the gating strategy to determine the frequency of SPB defined as CD20(PDF)Click here for additional data file.S3 Fig+ and ICOS- cmTFH cells (CD4+CD45RA-CXCR5+PD-1+) as a proportion of total CD4+ T cells.Representative flow plot, from an ART-treated HIV patient 7 days post-vaccination, showing the gating strategy used to determine the frequency of ICOS(PDF)Click here for additional data file.S4 FigA) IgG1 antibody to PcP 4, 6B, 9V and 14 (B) IgG2 to PcP 4, 6B, 9V and 14. Data are presented as fold-change in antibody levels between D0 and D28. Differences between groups were tested using Mann-Whitney tests. n.s., not significant and p<0.05 considered significant.((PDF)Click here for additional data file.S5 FigA) Proportions of ICOS+ cells in freshly isolated PBMC and cryopreserved PBMC correlate and (B) PD-1 staining using mAb clone EH12.2H7 (AF647) and MIH4 (APC) are comparable. Data were analysed by Spearman’s rank correlation test. Linear regression curves are shown for all data points (red line).((PDF)Click here for additional data file.S1 TableData are represented as correlation coefficient of % frequency at D7.(PDF)Click here for additional data file.S2 TableData represented as correlation coefficient of % frequency at D7.(PDF)Click here for additional data file.S3 TableData represented as correlation coefficient of % frequency at D7.(PDF)Click here for additional data file.S4 Table(PDF)Click here for additional data file.S5 Table(PDF)Click here for additional data file.S6 Table(PDF)Click here for additional data file.S7 TableData were analysed by Spearman’s rank correlation test.(PDF)Click here for additional data file.S8 Table(PDF)Click here for additional data file.


Tead1, Tead2 or Tead4 did not effect primary myoblast (PM) differentiation, but that their simultaneous knockdown strongly impaired differentiation. In contrast, Tead1 or Tead4 silencing impaired C2C12 differentiation showing their different contributions in PMs and C2C12 cells. Chromatin immunoprecipitation identified enhancers associated with myogenic genes bound by combinations of Tead4, Myod1 or Myog. Tead4 regulated distinct gene sets in C2C12 cells and PMs involving both activation of the myogenic program and repression of growth and signaling pathways. ChIP-seq from mature mouse muscle fibres in vivo identified a set of highly transcribed muscle cell-identity genes and sites bound by Tead1 and Tead4. Although inactivation of Tead4 in mature muscle fibres caused no obvious phenotype under normal conditions, notexin-induced muscle regeneration was delayed in Tead4 mutants suggesting an important role in myogenic differentiation in vivo. By combining knockdown in cell models in vitro with Tead4 inactivation in muscle in vivo, we provide the first comprehensive description of the specific and redundant roles of Tead factors in myogenic differentiation.The TEAD family of transcription factors (TEAD1-4) bind the MCAT element in the regulatory elements of both growth promoting and myogenic differentiation genes. Defining TEAD transcription factor function in myogenesis has proved elusive due to overlapping expression of family members and their functional redundancy. We show that silencing of either  in vitro. While the functions of recognised myogenic proteins such as Myogenin, Myod1 and MEF-family transcription factors in this process have been extensively studied, the role of the Tead factors has received only limited attention. Tead factors have well defined roles as mediators of Hippo signalling in promoting cell growth and oncogenic transformation, but are also involved in myogenic differentiation involving cell cycle arrest and activation of the myogenic gene expression program. Using integrative genomics and knockdowns in cell based models, we show that Tead factors are essential for differentiation of C2C12 cells and primary myoblasts, but make different contributions activating a distinct set of myogenesis genes in each cell type. We also developped effective chromatin immunoprecipitation from mature mouse muscle fibres allowing identification of highly transcribed muscle identify genes and identification of Tead1 and Tead4 occupied sites. Somatic inactivation in vivo revealed an important role for Tead4 in muscle fibre regeneration. The integration of genomics and loss of function in cell models in vitro and muscle in vivo provide the first comprehensive description Tead factors in myogenic differentiation.Aspects of muscle differentiation can be reproduced using the C2C12 cell line or primary myoblasts both of which can be differentiated to form myotubes  The TEAD1–4) transcription factors –4 transc bind to Tead4 promoter and activate its expression during C2C12 cell differentiation in vitro . Fo. Fo49]. GSM1354734. Myod1 and Myog ChIP-seq raw data were from GSE44824 [The public data for H3K27ac and H3K4me3 data were taken from the GEO accession GSE25308 , Jun GSES1 FigA-B. Immunoblots showing Tead1 or Tead4 protein levels in differentiating PMs (A) and C2C12 cells (B) transfected with the indicated siRNAs. Beta-actin is used as loading control. C Immunostaining for Tead1 and Tead4 in non-differentiated (ND) and differentiated C2C12 cells. Differentiated cells were counterstained with Myh to identify myotubes. Arrows indicate the nuclei of differentiated myotubes. D. Immunostaining for Tead1 and Tead4 in differentiated PMs. In the centre and right panels, cells were counterstained with Dmd to identify myotubes. The left panel shows a region where differentiated myotubes and non-differentiated PMs were intermixed allowing a comparison of the localisation of the proteins in the two states. All scale bars 100 μm.(TIF)Click here for additional data file.S2 FigA. UCSC genome browser shot of Tead4 occupancy at the Ctgf, Ccnd1 and Acta1 loci in differentiated and non-differentiated C2C12 cells. The Tead4-bound sites are indicated with arrows. B. Read density maps showing comparison of Tead4 binding with that of Jun, Runx and Srf.(TIF)Click here for additional data file.S3 FigA. Localisation of Tead1 occupied sites in non-differentiated C2C12 cells relative to genomic annotations and the TSS. B. Results of MEME analysis on the top 600 Tead1 occupied sites in non-differentiated C2C12 cells. Lower panel indicates the frequency of occurrence of DNA binding motifs for the indicated transcription factors at Tead1 occupied sites comparing the expected and observed values. C. Localisation of Tead1 occupied sites in differentiated C2C12 cells. D. UCSC genome browser view of Tead1 occupancy at the Ankrd1 and Vdr loci in the non-differentiated and differentiated state. E. Read density cluster map to compare Tead1 and Tead4 occupancy in non-differentiated cells.(TIF)Click here for additional data file.S4 FigA-B. UCSC screenshots showing Tead4 and Tead1 occupancy and H3K27ac at Tead1 and Tead4 gene loci in non-differentiated and differentiated C2C12 cells along with Myog and Myod1 occupancy in differentiated cells.(TIF)Click here for additional data file.S5 FigA. Immunostaining for Myh expression to show inhibition of C2C12 and PM differentiation following siMyog. B. RT-qPCR analyses of gene expression in siControl and siMyog C2C12 cells. C. UCSC screenshots showing Tead4 and Myog occupancy and H3K27ac at the Mef2c locus in differentiated C2C12 cells. Arrows indicate Tead4 or Myog bound sites that co-localise and/or co-localise with H3K27ac in differentiated cells.(TIF)Click here for additional data file.S6 FigA. Read density cluster map showing chromatin modifications at Tead1-occupied sites in non-differentiated cells. B. Venn diagrams illustrating the overlap of chromatin modifications with Tead1 genomic occupancy. C. Identification and ontology analysis of genes associated with Tead4 sites at active H3K27ac marked regulatory elements. D. UCSC screenshots showing Tead1, Tead4 occupancy and H3K4me3 and H3K27ac at a selection of loci illustrating constitutive and acquired chromatin marks and Tead binding during differentiation.(TIF)Click here for additional data file.S7 FigA. Read density cluster maps showing sites occupied by Myog, Myod1 and Tead4 in differentiated C2C12 cells. The metaprofiles of selected clusters are shown to the right. B. Read density cluster map comparing sites occupied by Myog and Myod1 in differentiated cells with Tead1 in non-differentiated cells. Only a small set of common sites was identified. C. Frequency of occurrence of transcription factor binding motifs at the commonly occupied sites from panel A. D. Venn diagrams illustrating the overlap of genes associated with Tead4, Myod1 and Myog bound sites. E-F. Read density cluster maps showing sites co-occupied by Tead4 or Tead1 and Mef2a. The metaprofiles of selected clusters are shown to the right.(TIF)Click here for additional data file.S8 FigA-B. Venn diagrams illustrating the overlap of up and down-regulated genes in differentiating PMs and C2C12 cells. The ontology analyses of the commonly regulated genes of both categories are shown.(TIF)Click here for additional data file.S9 FigA. Classification of gene expression changes into classes with different kinetics. B. GSEA analyses of genes up and down-regulated during C2C12 cell differentiation. The most significant categories are shown.(TIF)Click here for additional data file.S10 FigA. Classification of gene expression changes into classes with different kinetics. B. GSEA analyses of genes up and down-regulated during PM differentiation. The most significant categories are shown.(TIF)Click here for additional data file.S11 FigA. Venn diagram representing genes specifically or commonly down-regulated in C2C12 cells and PMs along with their BP-FAT ontology. B. Venn diagram representing genes specifically or commonly up-regulated in C2C12 cells and PMs along with their BP-FAT ontology.(TIF)Click here for additional data file.S12 FigA. Read density maps comparing Tead4 occupancy in muscle with that of Pol II and H3K27ac. The ontology of the genes associated with the subset of co-localising sites is indicated. B. Read density maps comparing Tead1 and Tead4 occupancy in muscle. The ontology of the genes associated with the subset of co-localising sites is indicated.(TIF)Click here for additional data file.S13 FigActa1 locus showing Tead1, Tead4, Pol II and H3K27ac ChIP-seq from WT and MT muscle. The arrow indicates the major Tead1/4 binding site.UCSC genome browser view of the (TIF)Click here for additional data file.S14 FigAmotl2 locus showing Tead1, Tead4, Myod and Myog occupancy and H3K27ac in differentiated C2C12 cells along with Tead1, Tead4, H3K27ac and Pol II in WT and MT muscle. Arrows indicate Tead1/4 bound sites common to both C2C12 cells and muscle.UCSC screenshots of the (TIF)Click here for additional data file.S15 FigA. Outline of experimental protocol showing days of Tam injection. B. RT-qPCR of the indicated genes. T-test; p-value * <0,05. N = 3. C. Tibialis anterior cross-section area of the indicated animals. Two-way anova, no significant values. N = 4. D. Tibialis anterior mass of the indicated animals. Two-tailed t-test, no-significant values. E. Grip strength of the indicated animals. no-significant values.(TIF)Click here for additional data file.S1 DatasetMACS ouput files with peak coordinates of Tead1 and Tead4 Chip-seq.(XLSX)Click here for additional data file.S2 DatasetPeak coordinates of Tead4 sites co-localising with Myog and Myod1.(XLSX)Click here for additional data file.S3 DatasetGenes de-regulated by siTead1/4 silencing in C2C12 cells.(XLSX)Click here for additional data file.S4 DatasetGenes de-regulated by siTead1/4 silencing in PMs.(XLSX)Click here for additional data file.S5 DatasetTead1/4 silencing in PMs and C2C12 cells.Ontology analyses of genes commonly or specifically regulated by si(XLSX)Click here for additional data file.S6 Dataset(XLSX)Click here for additional data file.


Aegilops geniculata (MgUg) is an important wild relative with several useful traits that can be exploited for wheat improvement. Screening of Ae. geniculata addition lines indicated a negative effect of 1Ug and the positive effect of 1Mg chromosome on wheat dough strength. Negative effect of 1Ug is probably associated with variation in number and position of the tripeptide repeat motif in the high molecular weight glutenin (HMW-G) gene. To utilize the positive potential of 1Mg chromosome, three disomic substitution lines (DSLs) 1Mg(1A), 1Mg(1B) and 1Mg(1D) were created. These lines were characterized for morphological, cytogenetic properties and biochemical signatures using FISH, 1D-, 2D-PAGE and RP-HPLC. Contribution of wheat 1A, 1B and 1D chromosomes towards dough mixing and baking parameters, chapatti quality, Fe/Zn content and glume color were identified. Observed order of variation in the dough mixing and baking parameters {1Mg(1D) ≤wheat ≤1Mg(1B) ≤1Mg(1A)} indicated that chromosome specific introgression is desirable for best utilization of wild species’ potential.Wheat cultivars with wide introgression have strongly impacted global wheat production.  Triticum aestivum L., 2n = 42; AABBDD) is the most widely cultivated crop in the world. Its technological properties are critical for product specific utilization. Globally, a relatively narrow genetic base hampers wheat improvement by limiting its end use quality. Useful genetic variation can be transferred to wheat from its related wild species that act as an excellent reservoir of a number of economically important genes. One such wild relative is tetraploid Aegilops geniculata  [Ae. geniculata is its ecological adaptability. It exhibits high genetic variation [Among the cereals, wheat (gMgUgUg) ,2. One oariation ,4 and syariation  that is ariation ,7,8.Ae. geniculata (bigger seeds) in the genetic background of Chinese Spring (CS) wheat. After selecting 1Mg addition line as a positive contributor for bread-making quality, we have produced all three chromosome specific substitution lines. Detailed grain quality analysis of these lines was carried out to understand the genetics and influence of homoeologous group-1 chromosomes and their encoded seed storage proteins (SSPs) on wheat processing and product quality.Considerable research had been conducted on wheat, to uncover the genetic basis of superior bread quality traits such as dough mixing properties, viscoelasticity, loaf volume and loaf score ,10. MixtAe. geniculata  in the genetic background of CS  were obtained from the germplasm bank for National Bioresource Project-Wheat (TACBOW 0283–0294), Japan [Ten DALs of g(1D) appeared spontaneously from the progeny of addition line. Screening and selection procedure included grain quality analysis, electrophoresis of glutenin and gliadin proteins and cytological analysis.DSL1Mg addition line was crossed with CS genetic stock-nullisomic for chromosome 1A and tetrasomic for chromosome 1B (N1A-T1B) in the year 2007–2008. Seeds of F1 plants were harvested in the year 2008, off season. F2 seeds were screened to identify DSL1Mg(1A). Screening procedure included electrophoresis of glutenin and gliadin proteins and cytological analysis of F2 seeds. Selected embryos were transferred to soil to raise F2 plants (year 2008–2009). Several F3 seeds derived from individual F2 plants were screened similarly for the confirmation of DSL1Mg(1A) F2 plants. Confirmed F3 seeds were sown and F4 seeds were harvested in the subsequent off season.For the generation of chromosome specific substitution line, 1Mg(1B) substitution line, CS genetic stock-N1B-T1D was crossed with DSL1Mg(1D) (year 2007–2008). F2 seeds were raised from F1 seeds in year 2008 off season and screened to identify DSL1Mg(1B). Further, the F3 seeds were raised in the same field in year 2008–2009 and screened for confirmation of the DSL1Mg(1B) F2 plants. F3 seeds from the confirmed F2 plants were sown to obtain F4 seeds in the 2009 off season.For generation of DSL1M4 seeds of all three substitution lines and CS was carried out in the field and greenhouse, at the International Center for Agricultural Research in Dry Areas (ICARDA), Syria in the fifth year (2009–2010). F5 seeds thus obtained were verified by rheological analysis at ICARDA. The seeds of CS and substitution lines were regrown in three replications in 2 meter rows (minimum one row) at the farms of National Agri-Food Biotechnology Institute (NABI), India in the sixth year , seventh , eighth  and ninth year . F7 seeds were used for bread-making quality analysis at Punjab Agricultural University (PAU), Ludhiana, Punjab, India. F9 seeds were used for bread- and biscuit-making quality analysis at Directorate of Wheat Research (DWR), Karnal, Haryana, India and at NABI, Mohali, Punjab, India. All the tests were carried out with three biological and three technical replicates.Replicated sowing of F°C. A linear gradient was set up using solvents A (0.1% TFA in HPLC grade water) and B (0.1% TFA in Acetonitrile). Glutenins were separated at a linear gradient 0% to24% B for 20 minutes and then 24% to 60% B for 40 minutes. Gliadins were separated from 20% to 60% B for 60 minutes. The peaks were detected at 210 nm by diode array UV-Vis detector.The seeds of CS, addition and substitution lines were characterised for different parameters. Total seed storage proteins were extracted according to Smith and Payne  by usinghttp://protcalc.sourceforge.net/).Full length HMW-GS genes were amplified , cloned,During the first year, grain testing of stable addition lines was carried out at Tottori University, Japan. Protein content was measured by near infrared (NIR) spectroscopy. Small-scale sodium dodecyl sulfate-sedimentation (SDSS) values were measured and specific sedimentation was calculated ,25.g and CS was performed at the National Agricultural Research Center for Western Region (NARCWR), Fukuyama, Japan. American Association of Cereal Chemists  methods [During the second year, grain quality analysis of DAL1M methods  were fol methods . Briefly methods . Ten gra methods .5 seeds of the substitution lines was carried out at ICARDA, Syria. The AACC (1990) [7 seeds was carried out at PAU, India. Grain characteristics were determined by standard laboratory procedures. Bread baking was carried out according to remixing procedure of Irrivine and McMullan [9 seeds of same material were studied at DWR, India, following AACC (1990) methods [During the fifth year, grain quality analysis of the FC (1990)  methods McMullan . In the  methods . Chapatt methods . Grain I methods . Gliadinin situ hybridization (GISH) with genomic DNA of Ae. geniculata as the probe was performed for confirmation of 1Mg chromosome [Ae. tauschii (D) and FISH with pAs1 (D genome specific sequences) [T. durum (AB) was used as the blocking DNA.Genomic romosome . The idequences) . Total gTo minimize the environmental and inter-laboratory variations and to determine the level of significance of the different parameters between the lines, analysis of variance (ANOVA) or analysis of covariance (ANCOVA) was carried out using the Stat view program.Ae. geniculata  were used for the initial screening. Glutenin profiles of ten DALs indicated two additional HMW-GSs each in DAL1Mg and DAL1Ug  HMW-GS sequences were compared with wheat and related wild species. Sequences showing a better match with HMW-GS genes of Ae. comosa (MM), were selected to represent 1Mgx (KX375404) and 1Mgy (KX375405) sequences. Those showing a better match with Ae. umbellulata (UU), were selected to represent 1Ugx (KX375406) and 1Ugy (KX375407) sequences. Analysis of the derived amino acid sequences indicated typical primary structure as previously reported with conserved signal peptide, N- and C-terminal regions, central repetitive domain and a similar number of cysteine residues  compared to 1Mgy (0.09) and wheat sequences (0.07). In case of x-type genes, it was uniform (0.056) with an exception of 1Ax (0.087). Multiple tripeptide repeats QQQ observed in y-type wheat sequences, was neither found in 1Mgy nor 1Ugy sequences. Three nonapeptides unique to wheat had three gutamine residues, (QQQ), while three nonapeptides unique to 1Ugy had only single glutamine residue . Another important and unique observation was deletion of GQQ tripeptide before the cysteine carrying nonapeptide repeat in the repetitive domain close to the C-terminal domain in 1Ugy and other U-genome HMW-GS sequences (AF476962.1). Hence, a regular sequence of (PGQGQQGHCPTSPQQ) was converted to (PGQGHCPTSPQQ).Calculated molecular weight (MW) and isoelectric point (pI) of 1Ug was higher than background cv. CS (1.36 vs. 0.84) and rest of addition lines indicating higher dough strength. DAL1Ug showed lower value than CS  and in greenhouse (1.25 vs. 0.85). Assessment of DAL1Mg in comparison to CS at NARCWR, Japan, indicated significantly higher SDSS, mixing peak height, and peak band width of DAL1Mg in comparison to CS  disomic substitution lines DSL1Mg(1D). Another replicate, with normal expression of Glu-D1 encoded subunits, had significantly higher SDSS/E-SDSS values than CS (g(1D) revealed two Ae. geniculata chromosomes (Ae. tauschii (D-genome donor) and pAs1 (D-genome specific sequences) revealed twelve D-genome chromosomes rather than regular fourteen in DSL1Mg(1D) (g(1D).During the third year, several DAL1M than CS . It was omosomes . FurtherL1Mg(1D) . pAs1 sig(1D) were similar to CS. Mixograph properties showed significant decrease in mixing peak time in comparison to CS } and 1B {DSL1Mg(1A)} were created.To utilize the potential of chromosome 1Mg(1A), DAL1Mg was crossed with N1A-T1B  gave six signals  in first and four  in second plant. The second plant with total 42 chromosomes, two each of 1Mg and 1B and missing 1A was selected and grown to raise the F3 seeds (3 seeds confirmed F2 plant as a stable substitution line {DSL1Mg(1A)}.To generate DSL1M N1A-T1B . The F1 F3 seeds . Uniformg(1B), CS genetic stock N1BT1D was crossed with DSL1Mg(1D)  gametes. F1 plants would only be double monosomic for chromosomes 1Mg and 1B. Screening for DSL1Mg(1B) was initiated at F2 stage. Out of the 20 analyzed seeds, 7 carried the 1Mg-encoded HMW-GSs as well as gliadins and did not carry chromosome 1B encoded glutenins and gliadins. GISH analysis using Ae. geniculata genomic DNA as probe revealed single Ae. geniculata chromosome in four and two in three embryos. Fluorescence in situ hybridization (FISH) analysis with the 45S rDNA probe  . Later wNA probe  gave twoomosomes  were selAe. geniculata as well as wheat homoeologous group-1 chromosomes on wheat technological properties.Substitution lines were characterized by analyzing their morphological, biochemical, rheological and baking properties and by understanding the influence of Ae. geniculata were morphologically similar to CS. DSL1Mg(1D) flowered earlier than others. DAL1Mg and all DSLs had black glume whereas, DSL1Mg(1B) had darkest glume among the tested lines (Addition as well as substitution lines of ed lines .g and DSL1Mg(1A) had six HMW-GSs, four from CS  and two from Ae. geniculata  {1Dx2, 1Dy12, 1Mgx, 1Mgy} as well as DSL1Mg(1D) {1Bx7, 1By8, 1Mgx, 1Mgy} had four HMW-GSs. Gliadin profile (Gli-Mg1 gliadin locus in the addition and substitution lines (3 in the ω-gliadin and 1 in α-gliadin region). DSL1Mg(1A) showed two missing bands in the α-gliadin range. DSL1Mg(1B) had three missing bands in α-gliadin and two in ω-gliadin region. DSL1Mg(1D) had one missing band each in the α-gliadin and ω-gliadin region.DAL1M profile  indicateg, 1Mgx with two spots had an acidic pI near 1Dx2 and 1Mgy with three spots had a higher pI near 1Bx7 (g(1B) and DSL1Mg(1D) corresponding wheat HMW-GSs were missing (g(1A) all the HMW-GSs were identified , DSL1Mg(1B) and DSL1Mg(1D) revealed 1, 4, 8 and 7 missing and 1, 1, 2, 4 relatively reduced expression bands, respectively.Several differences were observed in 2D-PAGE total protein profiles of CS, DAL and DSLs . In CS fear 1Bx7 . In the  missing . In DSL1entified . In CS, g coded HMW-GS peaks. Second 1B and 1Mg coded peaks observed in 1D- and 2D-PAGE could not be separated in the RP-HPLC  that might be the reason for the lower gliadin/glutenin ratio in DSL1Mg(1A) as compared to CS and other DSLs.RP-HPLC of glutenins and gliadin proteins of CS and DSLs was carried out to estimate their relative expression. Glutenin profile indicated two 1D coded, single 1B coded and single 1M RP-HPLC . LMW glun region . The α-,omosomes . Out of g(1D), than CS as revealed by lower dough development time (DDT), stability time (ST) and higher softening (g(1A) had highest dough strength, as revealed by higher DTT, ST and lower softening. Dough strength of DSL1Mg(1B) was higher than CS but lower than DSL1Mg(1A). Protein content of DSLs was similar to CS. Their seeds were smaller and harder than CS. Similar results were obtained from the greenhouse grown samples  seeds indicated significantly reduced dough strength in DSL1Moftening . DSL1Mg( samples .g(1B) and DSL1Mg(1D) was lower than CS (g(1A) was higher than CS and other DSLs. Bread loaf studies indicated significantly higher loaf volume as well as loaf score in DSL1Mg(1A) compared to CS and rest of substitution lines. Differences were observed in the environmentally controlled traits such as protein content, hardness and test weight. The protein content and hardness of DSL1Mg(1D) and CS were lower than DSL1Mg(1A), DSL1Mg(1B). The test weight of former was higher than the later.In the subsequent tested year,  gluten index of DSL1M than CS . Gluten g(1B), DSL1Mg(1D) and CS. Its value was significantly higher in DSL1Mg(1A). Bread loaf studies indicated slightly, but significantly higher bread loaf in the DSL1Mg(1A) compared with the rest of the lines. The loaf score of the line was significantly higher than the rest of the lines. Biscuit making studies indicated higher biscuit spread factor in DSL1Mg(1A) and DSL1Mg(1B). The sedimentation value of DSL1Mg(1D) was lower than CS and other lines. It was highest in DSL1Mg(1A) and followed by DSL1Mg(1B). Both these lines had higher sedimentation value than CS. Gliadin/glutenin ration was higher in DSL1Mg(1D) and lower in DSL1Mg(1A) in comparison to CS and DSL1Mg(1B). HMW-GS/LMW-GS was higher in DSL1Mg(1A) and DSL1Mg(1B). All lines had similar test weights. Grain hardness and protein content of DSL1Mg(1A) and DSL1Mg(1B) were slightly, but significantly lower than CS and DSL1Mg(1D). Chapatti making studies on the characterized lines indicated higher chapatti score in DSL1Mg(1D). In particular, this line had better rolling and puffing quality than others. Order of iron content was DSL1Mg(1A) > DSL1Mg(1B) >CS = DSL1Mg(1D) and zinc content was DSL1Mg(1B) > DSL1Mg(1A) >CS = DSL1Mg(1D).Third year analysis of field grown lines in Punjab, India  revealedg chromosome of Ae. geniculata and negative influence of its 1Ug chromosomes on wheat flour mixing properties. Reduction in dough mixing property by 1Ug HMW-GSs is expected to be associated with tripeptide repeat motif numbers, sequence, distribution and position in the protein on the basis of sequence comparison. Chromosome specific DSLs were created in this work. Study of DSLs indicated the importance of chromosomes 1A and 1D for dough mixing properties. Baking studies indicated that the potential of 1Mg proteins to improve bread making quality can be best utilized by substitution with corresponding chromosome 1A loci.This study reports positive influence of 1MAe. geniculata DAL1Ug and DAL1Mg with reduced and improved dough strength. Thus Ae. geniculata DALs were selected for further study. From ten available Ae. geniculata addition lines in wheat, we identified DAL1Ug and DAL1Mg with additional HMW-GSs and gliadins. The HMW-GSs are major determinants of wheat processing quality. In the HMW-GSs number of cysteine residues involved in the intermolecular disulphide bridges and the length of the repetitive domain involved in β-sheet structure and H-bonds have been reported to affect gluten macropolymer and flour technological parameters [g compared to CS, as it carried two additional HMW-GSs with long repetitive domain and typical number of cysteine residues. In this case, it could be better explained with pI, glutamine content, distribution of repeat motif, especially near the cysteine residues involved in intermolecular disulphide bonding [g, HMW-GS genes had lower pI than corresponding DAL1Mg and wheat sequences. More acidic proteins are expected to form a lower number of H-bonds [g. Another important observation was absence of GQQ tripeptide before the nonapeptide repeat with cysteine amino acid, in the repetitive domain close to the C-terminal domain. It might be affecting its tertiary structure and therefore availability of cysteine residue for intermolecular bonding with other HMW- and LMW-GSs [Ae. umbellulata chromosome 1U addition line with reduced dough strength, in spite of addition of HMW-GSs with longer repetitive domain and typical number and position of cysteine residues.The contribution of homoeologous group-1 and their HMW-G genes towards bread making quality has been well documented ,14,32. Arameters ,34,35. H bonding ,37. The  H-bonds . Higher  LMW-GSs . The impg had improved dough strength than CS as indicated by higher SDSS value, UPP, mixing peak height and mixing peak width with non-significantly different protein content that was maintained across environments. It must be associated with chromosome 1Mg coded proteins of Ae. geniculata. As, among the wheat proteins, polymeric glutenins especially HMW-GSs are major contributors towards dough mixing and baking properties [g might be contributing towards improved dough strength of DAL1Mg. The next step of confirmation and utilization of contributing proteins of wild chromosome is to create chromosome specific substitution lines and study their mixing and baking properties. Studies on created DSLs across environments indicated drastic improvement and reduction in mixing parameters in DSL1Mg(1A) and DSL1Mg(1D), respectively, with small but statistically significant improvement in DSL1Mg(1B). It was evident from mixographic and UPP studies in Tottori, Japan, farinographic studies in Aleppo, Syria and gliadin/glutenin ratio, HMW-GS/LMW-GS ratio and gluten index in Punjab and Haryana, India. DSL1Mg(1D) showed significantly reduced peak mixing time, glutenin macropolymer, farinograph development time, stability time, gluten index and glutenin/gliadin ratio compared to CS. DSL1Mg(1B) had improved farinograph development time, stability time and HMW-G/LMW-G ratio but with non-significantly different gluten index and glutenin/gliadin ratio. DSL1Mg(1A) showed drastically improved farinograph development time, stability time, gluten index, glutenin/gliadin ratio and HMW-GS/LMW-GS ratio. Baking studies indicated improved loaf volume and loaf score in DSL1Mg(1A) with non-significant differences in DSL1Mg(1B) and DSL1Mg(1D). Our study highlights the importance of chromosome 1D for wheat mixing and baking parameters. It will be possible to improve technological properties of wheat by wide introgression if transferred to chromosome 1B or 1A. The effect will be a drastic improvement with chromosome 1A specific transfer and significant improvement in 1B transfer [g(1D) is an important observation that can help in understanding different genes involved in relatively less studied chapatti making quality. DSL1Mg(1D) showed very low gluten index that may be associated with its better chapatti making quality. Improvement in observed biscuit spread factor in DSL1Mg(1A) and DSL1Mg(1B) was due to reduced protein content in these lines in the studied year.Differences in mixing strength and baking performance among different wheat genotypes largely reside in the insoluble glutenin fraction of endosperm proteins ,40. Peakoperties ,43, thertransfer . Improveg(1A) and DSL1Mg(1B) than others, indicating the influence of environment on protein content. Similar environmental influence was observed for grain size and hardness.Grain size, protein content and hardness show genotype by environment effect . ProteinHigher genotype effect than the environment effect had been reported in mixing properties than baking qualities. These parameters are usually controlled by several genes with different effects called quantitative trait loci (QTL). The QTLs for the mixographic peak time had been reported on 1DL, 1B, 2D, 2B, 2AL, 7AS and 7DS chromosomes ,46. Our Rg genes (red glume) located on 1AS, 1BS and 1DS in hexaploid wheat and Bg genes (black glume) on 1AS and 1DS in durum and synthetic wheat [g, DSL1Mg(1D) and DSL1Mg(1A) has a black glume color, the darkest being in the DSL1Mg(1B). This was due to black glume color genes associated with chromosome 1Mg of Ae. geniculata [Rg and Bg loci in wheat. The primary effect of Bg-Mg1 is conditioned upon the presence of Bg-B1 locus that probably reduces the effect of Bg-Mg1 indicating conditional epistasis. To the best of our knowledge, due to genome complexity in wheat, a gene specific epistasis effect is being reported here for the first time.The genes/QTLs may influence the trait positively, negatively or through epistatic interactions ,48. Glumic wheat . Spikes niculata  that mayg(1D) appeared spontaneously, combination of biochemical protein markers with cytological markers helped in the development of DSLs in three generations only. Combination of different protein separation techniques viz. 1D-PAGE, 2D-PAGE and RP-HPLC helped in assignment and calculation of number of proteins coded by 1A, 1B and 1D chromosomes. The overall number of 1B coded storage proteins was higher than others, with higher number of γ-gliadins and lower number of LMW-GSs. While PAGE detected a lower number of 1A coded proteins, HPLC indicated their expression to be equivalent to 1D and 1Mg. Improvement in mixing properties in DSL1Mg(1B) is probably due to reduction in gliadins leading to higher glutenin/gliadin ratio. In the DSL1Mg(1A) it might be due to increase in number of HMW-GSs i.e., six compared to four in DSL1Mg(1B) and DSL1Mg(1D) and creation of better gluten macro-polymer by formation of higher intermolecular disulphide- and H-bonds.Creation of DSLs is tedious and time consuming. While DSL1M1D-PAGE could effectively separate HMW-GS and ω-gliadins. 2D-PAGE could better separate different proteins compared to 1D-PAGE, but it was more tedious. RP-HPLC was a better technique for the separation of LMW-GSs and α-, γ- gliadins. Since in the present investigation DAL and DSLs were in the soft wheat CS background and is not suitable for bread making quality, therefore, it will be interesting to generate these DSLs in the hard wheat background and study their influence on mixing and baking qualities in wheat.g of Ae. geniculata showed positive influence and DAL1Ug negative influence on wheat dough strength. Based on sequence comparison, the dough strength reduction by 1Ug HMW-GSs is probably associated with the tripeptide repeat motif number, sequence, distribution and position in the gene. Chromosome specific DSLs were created and analyzed. Study of DSLs indicated the importance of chromosomes 1A and 1D for dough mixing properties. The potential of Glu-Mg1 proteins for bread quality improvement can be best utilized by replacement with corresponding chromosome 1A loci of wheat.DAL1MS1 Fig(TIF)Click here for additional data file.S2 FigNote the missing 1D HMW-GSs and corresponding reduction in specific sedimentation.(TIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.