Authenticated DNA from Ancient Wood Remains

• Background The reconstruction of biological processes and human activities during the last glacial cycle relies mainly on data from biological remains. Highly abundant tissues, such as wood, are candidates for a genetic analysis of past populations. While well-authenticated DNA has now been recovered from various fossil remains, the final ‘proof' is still missing for wood, despite some promising studies. • Scope The goal of this study was to determine if ancient wood can be analysed routinely in studies of archaeology and palaeogenetics. An experiment was designed which included blind testing, independent replicates, extensive contamination controls and rigorous statistical tests. Ten samples of ancient wood from major European forest tree genera were analysed with plastid DNA markers. • Conclusions Authentic DNA was retrieved from wood samples up to 1000 years of age. A new tool for real-time vegetation history and archaeology is ready to us

Radiative and mechanical feedback into the molecular gas in the Large Magellanic Cloud. I. N159W

We present Herschel SPIRE Fourier Transform Spectrometer (FTS) observations of N159W, an active star-forming region in the Large Magellanic Cloud (LMC). In our observations, a number of far-infrared cooling lines including CO(4-3) to CO(12-11), [CI] 609 and 370 micron, and [NII] 205 micron are clearly detected. With an aim of investigating the physical conditions and excitation processes of molecular gas, we first construct CO spectral line energy distributions (SLEDs) on 10 pc scales by combining the FTS CO transitions with ground-based low-J CO data and analyze the observed CO SLEDs using non-LTE radiative transfer models. We find that the CO-traced molecular gas in N159W is warm (kinetic temperature of 153-754 K) and moderately dense (H2 number density of (1.1-4.5)e3 cm-3). To assess the impact of the energetic processes in the interstellar medium on the physical conditions of the CO-emitting gas, we then compare the observed CO line intensities with the models of photodissociation regions (PDRs) and shocks. We first constrain the properties of PDRs by modelling Herschel observations of [OI] 145, [CII] 158, and [CI] 370 micron fine-structure lines and find that the constrained PDR components emit very weak CO emission. X-rays and cosmic-rays are also found to provide a negligible contribution to the CO emission, essentially ruling out ionizing sources (ultraviolet photons, X-rays, and cosmic-rays) as the dominant heating source for CO in N159W. On the other hand, mechanical heating by low-velocity C-type shocks with ~10 km/s appears sufficient enough to reproduce the observed warm CO.Comment: accepted for publication in A&

Measurement and comparison of individual external doses of high-school students living in Japan, France, Poland and Belarus -- the "D-shuttle" project --

Twelve high schools in Japan (of which six are in Fukushima Prefecture), four in France, eight in Poland and two in Belarus cooperated in the measurement and comparison of individual external doses in 2014. In total 216 high-school students and teachers participated in the study. Each participant wore an electronic personal dosimeter "D-shuttle" for two weeks, and kept a journal of his/her whereabouts and activities. The distributions of annual external doses estimated for each region overlap with each other, demonstrating that the personal external individual doses in locations where residence is currently allowed in Fukushima Prefecture and in Belarus are well within the range of estimated annual doses due to the background radiation level of other regions/countries

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Hapstep

This TURBO PASCAL program is based on the more simple program called HaPermut, except that analyses can be made in a stepwise manner, by combining related haplotypes progressively, as explained in the paper by Odile Pons and Rémy J. Petit (Genetics 1996, 144:1237-1245). Here are the same explanations than in HaPermut: HaPermut computes measures of diversity and differenciation from haploid population genetic data, when a measure of the distance between haplotypes is available, and test whether the differentiation and diversity measures differ from the equivalent measures that do not take into account the distances between haplotypes (ie, that consider all haplotypes equally divergent). The source file should be an ASCII file (its name should have 8 characters maximum: 12345678.txt) and should include the following information: First line : Number of cytotypes Number of populations Number of characters distinguishing the variants (for instance number of polymorphic fragments, or of polymorphic nucleotide sites). The program asks for the number of permutations to be made. see the example (instep.txt and outstep.out). The program is dimensionned for a maximum number of 50 cytotypes, 100 populations, and 40 characters. If you have more than this, it means the PASCAL program permut2.pas should be modified accordingly and re-compiled. Then follows the number of individuals having a given cytotype (column) in a given population (row). Finally, and without interruption, provide the table of character states for all haplotypes, where each line corresponds to one haplotype, and each column to a character. No column should be empty (no missing haplotype) and each population (row) should be composed of AT LEAST 3 individuals! The output file provides permutated values of Nst in a single row, and the value of the last 5% and last 1%. The mean of the permutated values is also given and should be close to the Gst value (by construction). To test if the observed Nst value is larger than the Gst, we count how many permutated values are larger than the observed Nst. If you have 5% of the permutated values greater than the observed value of Nst, then your test is not significant, otherwise it is and you know the P-value. This is akin to testing if Gst = Nst

Rarefac

This programme (RAREFAC) is written in Turbo-Pascal and relates to the following paper : Petit, El Mousadik & Pons. 1998. Identifying populations for conservation on the basis of genetic markers. Conservation Biology 12, 844-855. It is a simplified version of the programme CONTRIB providing just the option of rarefaction and the partitioning of allelic richness within and among populations. This is contrasted with equivalent measurements for H, the expected heterozygosity. It can be used in conjunction with the program haplodiv based on the paper by Pons & Petit 1995, TAG 90, 462-470, which will provide standard errors for the diversity and differentiation parameters. The input file is a text file, where the first line indicates the number of haplotypes (limited to 100), then the number of populations (limited to 50), and finally the rarefaction size (it should not be larger than the smallest population sample size. Then follows the data for each population (line), with the number of each haplotype in each population (don't use relative frequencies). Example: 18 4 10 1 0 1 0 0 0 1 1 ...(18 columns) 0 1 2 1 1 0 13 0 ... 0 0 8 0 0 3 6 0 ... 1 0 9 0 0 3 7 1 Results can be seen in the output file. General measures are given first: Within population diversity (HS), total diversity (HT), and GST are given, followed by similar measures based on allelic richness. Then you get the results for each population: H, its standard error, and allelic richness after rarefaction (minus one: a monomorphic population has one allele which has to be removed to compute the partitioning of diversity within and among populations). The program is written for an haploid gene but may be used for nuclear genes, assuming Hardy-Weinberg equilibrium. How to proceed when there are several loci? Do not take the mean across Gst or Rst. They are ratios, so you should take the mean of the numerator and the mean of the denominator separately. Then compute the ratio of the two means.

DistoN

This TURBO PASCAL program DistoN yields pairwise estimates of diversity that can be used to measure Gst or Nst as a function of distance. These measures are based on haploid population genetic data, when the difference in number of repeats between alleles is available. The source file should be an ASCII file (its name should have 8 characters maximum: 12345678.txt) and should include the following information : First line : Number of cytotypes Number of populations Number of characters (loci, polymorphic fragments...). Then follows the number of individuals having a given haplotype (column) in a given population (row). Finally, and without interruption, provide the table of length variant states for all haplotypes, where each line corresponds to one haplotype, and each column to a character. No column should be empty (no missing haplotype) and each population (row) should be composed of AT LEAST 3 individuals! The output file provides the number of the two populations compared, followed by values of pairwise hs, ht, vs, vt in a single row. To see if Gst or Nst changes with distance, compute separetely the distance (in km for instance) between populations, and compute mean values of these four estimates for each distance class. Then derive Gst (or Nst) for that distance class as: 1-mean hs/ mean ht (or 1-mean vs/mean vt)

Polymorphisme de l'ADN chloroplastique dans un complexe d'especes: les chenes blancs europeens. Subdivision de la diversite des genes cytoplasmiques chez les plantes

SIGLEAvailable from INIST (FR), Document Supply Service, under shelf-number : T 82591 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

Logiciels Permut et cpSSR

THE PROGRAM PERMUT AND THE PROGRAM CpSSR BECOME ONLY ONE PROGRAM. When you run the program you can choose if you want to use permut or CpSSR. README PERMUT This program is based on the papers (Pons & Petit Genetics 1996, 144:1237-1245) and (Burban et al. 1999, Mol Ecol 8, 1593-1602). It computes measures of diversity and differenciation from haploid population genetic data, when a measure of the distance between haplotypes is available, and test whether the differentiation and diversity measures differ from the equivalent measures that do not take into account the distances between haplotypes (ie, that consider all haplotypes equally divergent). The source file should be an ASCII file (its name should have 8 characters maximum: 12345678.txt) and should include the following information: First line : Number of cytotypes Number of populations Number of characters distinguishing the variants (for instance number of polymorphic fragments, or of polymorphic nucleotide sites). The program asks for the number of permutations to be made. see the example (\ExamplePermut\input.txt and \ExamplePermut\output.out). Then follows the number of individuals having a given cytotype (column) in a given population (row). Finally, and without interruption, provide the table of character states for all haplotypes, where each line corresponds to one haplotype, and each column to a character. No column should be empty (no missing haplotype) and each population (row) should be composed of AT LEAST 3 individuals! The output file provides permutated values of Nst in a single row, and the value of the last 5% and last 1%. The mean of the permutated values is also given and should be close to the Gst value (by construction). To test if the observed Nst value is larger than the Gst, we count how many permutated values are larger than the observed Nst. If you have 5% of the permutated values greater than the observed value of Nst, then your test is not significant, otherwise it is and you know the P-value. This is akin to testing if Gst = Nst. README CpSSR : It computes measures of diversity and differenciation from haploid population genetic data, when the difference in number of repeats between alleles is available, and tests whether the differentiation and diversity measures differ from the equivalent measures when the distances between haplotypes is not considered (ie, when all haplotypes are considered equally divergent). The source file should be an ASCII file (its name should have 8 characters maximum: 12345678.txt) and should include the following information: First line : Number of cytotypes Number of populations Number of cpSSR loci. The program asks for the number of permutations to be made. See the example (\ExampleCpSSR\input.txt and \ExamplePermut\CpSSR.out). Then follows the number of individuals having a given haplotype (column) in a given population (row). Finally, and without interruption, provide the table of length variant states for all haplotypes, where each line corresponds to one haplotype, and each column to a character. No column should be empty (no missing haplotype) and each population (row) should be composed of AT LEAST 3 individuals! The output file provides permutated values of Rst in a single row, and the value of the last 5% and last 1%. The mean of the permutated values is also given and should be close to the Gst value (by construction). To test if the observed Rst value is larger than the Gst, you count how many permutated values are larger than the observed Rst. If you have 5% of the permutated values greater than the observed value of Rst, then your test is not significant, otherwise it is and you know the P-value. This is akin to testing if Gst = Rst. I usually go for a one-sided test (i.e. I test if Rst>Gst, and not RstGst)