Seasonal Variations in Vegetation Indices derived from in situ Type Vegetation Monitoring System at typical landcovers in Japan : From the Observation Results in PGLIERC and Lake Biwa Project

研究概要:本研究では光学センサー搭載衛星データの検証及び地表面フラックスとの対応関係を調べるために簡易式の地上設置型植生モニタリングシステムを日本を代表する土地被覆上(草地,水田,アカマツ林,落葉広葉樹)に設置し,それぞれの土地被覆から得られる植生指標の季節変化について示した.その結果,以下の知見が得られた;1.草原系(草地・水田)では各植生の季節変化特性を良好にモニターすることが可能である,2.森林系(アカマツ林・落葉広葉樹)ではセンサーとキャノピーの距離が近すぎるため,思うような結果を得ることが出来なかった.3.ただし全般としては各土地被覆特性を示す連続したデータを取得することができ,システムの妥当性を示すことができた

Additional file 2: of Overview of methodologies for T-cell receptor repertoire analysis

UMI filtering script (python). The script used to filter the unique molecular identifiers. (PY 4 kb

Additional file 2: of Overview of methodologies for T-cell receptor repertoire analysis

UMI filtering script (python). The script used to filter the unique molecular identifiers. (PY 4 kb

data.genotypes

The file contains the genotypes of all 948 individuals studied. Each row represents one individual.The first column gives the individual ID followed by the genotypes of all SNPs. Alleles are coded as 0, 1 or 2 representing 0, 1 or 2 copies of the A-Allele, respectively

data.genes

The file contains all SNP names and their location within a gene

Additional file 1: Figure S1. of Fitness consequences of polymorphic inversions in the zebra finch genome

Linkage disequilibrium and principal component analysis results along chromosomes Tgu2, Tgu26 and Tgu27. Figure S2. Composite LD between eigenvectors of PC1 to PC3 and the SNPs along chromosome Tgu5. Figure S3. Composite LD between eigenvectors of PC1 to PC3 and the SNPs along chromosome Tgu11. Figure S4. Composite LD between eigenvectors of PC1 to PC4 and the SNPs along chromosome Tgu13. Figure S5. Composite LD between eigenvectors of PC1 to PC5 and the SNPs along chromosome TguZ. Figure S6. Median-joining networks of phased SNPs for the inversions on chromosomes Tgu5, Tgu11, Tgu13 and TguZ. Figure S7. Diversity in 50 kb windows along each chromosome in the zebra finch genome. Figure S8. Dominance effects of mother’s and father’s inversion karyotype on embryo mortality in three captive populations. Figure S9. Additive effects of the minor inversion allele on different fitness parameters in three captive populations. Figure S10. Negative frequencydependent selection effects on different fitness parameters in two captive populations. Figure S11. Dominance effects of the minor inversion allele on morphological phenotypes in three captive and two wild populations. Figure S12. Composite LD along chromosome TguZ between all combinations of the three inversion haplotypes. Figure S13. Linkage disequilibrium and principal component analysis results along chromosomes Tgu5, Tgu11, Tgu13 and TguZ using a filtered SNP set. Figure S14. Principle component analysis results from the wild “Fowlers Gap” birds along chromosome Tgu5, Tgu11, Tgu13 and TguZ together with the founders of the three captive populations. Color coded are the inversion type calls for each individual using only the information from the tag SNPs as described in the Methodssection. Figure S15. Principle component analysis results from the wild “Fowlers Gap” birds along chromosome Tgu5, Tgu11, Tgu13 and TguZ with PCA scores of founder individuals of the three captive populations overlaid. (DOCX 8865 kb

A post-GWAS analysis of predicted regulatory variants and tuberculosis susceptibility

<div><p>Utilizing data from published tuberculosis (TB) genome-wide association studies (GWAS), we use a bioinformatics pipeline to detect all polymorphisms in linkage disequilibrium (LD) with variants previously implicated in TB disease susceptibility. The probability that these variants had a predicted regulatory function was estimated using RegulomeDB and Ensembl’s Variant Effect Predictor. Subsequent genotyping of these 133 predicted regulatory polymorphisms was performed in 400 admixed South African TB cases and 366 healthy controls in a population-based case-control association study to fine-map the causal variant. We detected associations between tuberculosis susceptibility and six intronic polymorphisms located in <i>MARCO</i>, <i>IFNGR2</i>, <i>ASHAS2</i>, <i>ACACA</i>, <i>NISCH</i> and <i>TLR10</i>. Our post-GWAS approach demonstrates the feasibility of combining multiple TB GWAS datasets with linkage information to identify regulatory variants associated with this infectious disease.</p></div

Frequencies of <i>C4B*Q0</i> carriers in healthy German individuals of different age-groups stratified for (a) smokers (current smokers and quitters <3 years) and (b) non-smokers (never smokers and quitters for ≥3 years).

<p>For abbreviations see legend to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0086188#pone-0086188-g001" target="_blank">Figure 1</a>. Due to the small number of centenarians in the replication sample we did not subdivide the case sample into a nonagenarian and centenarian subgroup.</p

Frequencies of <i>C4B*Q0</i> carriers (with zero or one <i>C4B</i> gene in the diploid genome) in healthy German individuals of different age-groups.

<p>p_case_contr: p value for the comparison of <i>C4B*Q0</i> carrier frequencies between long-lived cases and younger controls (Fisher's exact test; primary endpoint). p_contr_trend: p value for trend test of <i>C4B*Q0</i> carrier frequencies in the three control subgroups (Armitage trend test; secondary endpoint). p_case: p value for the comparison of <i>C4B*Q0</i> frequencies in the two case subgroups (Fisher's exact test; secondary endpoint). p_trend: p value for trend test of <i>C4B*Q0</i> frequencies in all five age groups (Armitage trend test; secondary endpoint).</p

Replication study in additional German sample: Results of the comparison of Q0 carrier state for the <i>C4L</i> gene (absolute numbers are in parentheses).

<p>For abbreviations see legend to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0086188#pone-0086188-t002" target="_blank">Table 2</a>.</p><p>p_trend: p value for trend test of <i>C4B*Q0</i> frequencies in all four age groups (Armitage trend test; secondary endpoint).</p>*<p>Due to the small number of centenarians in the replication sample we did not subdivide the case sample into a nonagenarian and centenarian subgroup.</p