A PM10 chemically characterised nation-wide dataset for Italy. Geographical influence on urban air pollution and source apportionment

: Urban textures of the Italian cities are peculiarly shaped by the local geography generating similarities among cities placed in different regions but comparable topographical districts. This suggested the following scientific question: can such different topographies generate significant differences on the PM10 chemical composition at Italian urban sites that share similar geography despite being in different regions? To investigate whether such communalities can be found and are applicable at Country-scale, we propose here a novel methodological approach. A dataset comprising season-averages of PM10 mass concentration and chemical composition data was built, covering the decade 2005-2016 and referring to urban sites only (21 cities). Statistical analyses, estimation of missing data, identification of latent clusters and source apportionment modelling by Positive Matrix Factorization (PMF) were performed on this unique dataset. The first original result is the demonstration that a dataset with atypical time resolution can be successfully exploited as an input matrix for PMF obtaining Country-scale representative chemical profiles, whose physical consistency has been assessed by different tests of modelling performance. Secondly, this dataset can be considered a reference repository of season averages of chemical species over the Italian territory and the chemical profiles obtained by PMF for urban Italian agglomerations could contribute to emission repositories. These findings indicate that our approach is powerful, and it could be further employed with datasets typically available in the air pollution monitoring networks

QTL mapping and candidate genes for resistance to Fusarium ear rot and fumonisin contamination in maize

Background: Fusarium verticillioides is a common maize pathogen causing ear rot (FER) and contamination of the grains with the fumonisin B1 (FB1) mycotoxin. Resistance to FER and FB1 contamination are quantitative traits, affected by environmental conditions, and completely resistant maize genotypes to the pathogen are so far unknown. In order to uncover genomic regions associated to reduced FER and FB1 contamination and identify molecular markers for assisted selection, an F2:3 population of 188 progenies was developed crossing CO441 (resistant) and CO354 (susceptible) genotypes. FER severity and FB1 contamination content were evaluated over 2years and sowing dates (early and late) in ears artificially inoculated with F. verticillioides by the use of either side-needle or toothpick inoculation techniques. Results: Weather conditions significantly changed in the two phenotyping seasons and FER and FB1 content distribution significantly differed in the F3 progenies according to the year and the sowing time. Significant positive correlations (P < 0.01) were detected between FER and FB1 contamination, ranging from 0.72 to 0.81. A low positive correlation was determined between FB1 contamination and silking time (DTS). A genetic map was generated for the cross, based on 41 microsatellite markers and 342 single nucleotide polymorphisms (SNPs) derived from Genotyping-by-Sequencing (GBS). QTL analyses revealed 15 QTLs for FER, 17 QTLs for FB1 contamination and nine QTLs for DTS. Eight QTLs located on linkage group (LG) 1, 2, 3, 6, 7 and 9 were in common between FER and FB1, making possible the selection of genotypes with both low disease severity and low fumonisin contamination. Moreover, five QTLs on LGs 1, 2, 4, 5 and 9 located close to previously reported QTLs for resistance to other mycotoxigenic fungi. Finally, 24 candidate genes for resistance to F. verticillioides are proposed combining previous transcriptomic data with QTL mapping. Conclusions: This study identified a set of QTLs and candidate genes that could accelerate breeding for resistance of maize lines showing reduced disease severity and low mycotoxin contamination determined by F. verticillioides

QTL MAPPING OF MAIZE RESISTANCE TO EAR ROT AND MYCOTOXIN CONTAMINATION CAUSED BY FUSARIUM VERTICILLIOIDES USING GENOTYPING BY SEQUENCING

Fusarium verticillioides (FV) is a fungal maize pathogen that causes Fusarium ear rot (FER) and contaminates the grains with fumonisins, a family of carcinogen mycotoxins. Maize genotypes show quantitative genetic variations for resistance to FER and fumonisin B1 (FB1) accumulation. Moreover both traits have moderate -high heritability. For these reasons Marker Assisted Selection of resistant genotypes is an attractive approach to reduce the losses derived from this fungal infection. The outcome of the infection is strongly influenced by environmental conditions and the disease severity vary greatly among years. A careful phenotyping of the population has a central role in a precise QTL mapping of traits related to resistance to FER and FB1 accumulation. The resistant (CO441) and the susceptible (CO354) lines to FV infection were crossed and generated 180 F2:3 segregant maize families. The population was evaluated for resistance to FER and FB1 accumulation in two sowing times, early and late, of both 2011 and 2012. Phenotyping was conducted on artificially inoculated F3 ears at 15 days after pollination with two methods (sideneedle, inoculation with spores, and toothpick, inoculation with mycelium). FER resistance was evaluated at maturity using a 1-7 rating of Fusarium infection on the ears, corresponding respectively to 0 and 100% of the infected ear. FB1 accumulation in the grains was predicted by NIR spectroscopy. In parallel, a molecular linkage map was constructed for the CO441xCO354 progeny (157 F3 DNA pools and the parents) using a Genotyping-by-Sequencing (GBS) approach (PLoS ONE 6(5):e19379). Initial analyses identified 16.236 SNP markers. Stringent criteria for SNP calling and filtering, segregation distortion and the setting of a threshold for missing data generated a set of 339 SNPs. These markers were integrated with genotyping data from 72 SSRs to construct a more dense linkage map. A total of 16 and 14 QTLs for FER resistance and FB1 accumulation were detected using MQM analysis, and 5 of them were overlapped between the two traits. These small-moderate effect QTLs were mainly detected in 1, 2, 4-9 maize chromosomes

Genotyping by sequencing and QTL mapping for Fusarium ear rot resistance and fumonisin B1 accumulation in maize.

Fusarium verticillioides is the causal agent of Fusarium ear rot (FER) in maize and contaminates the grains with fumonisins, a family of mycotoxins that affects feed and food. Quantitative genetic variations exists for resistance to FER and fumonisin B1 accumulation among maize genotypes. Both traits have moderate to high heritability and Marker Assisted Selection of resistant genotypes is an attractive approach to control this problem in maize crops. In order to genetically dissect FER responses in maize and identify molecular markers associated with resistance loci, a cross from the resistant CO441 and the susceptible CO354 parents was generated and F2:3 segregant maize families were evaluated for resistance to FER and fumonisin B1 accumulation in both 2011 and 2012. Phenotyping was conducted on artificially inoculated F3 ears at 15 days after pollination (DAP) with two side-needle inoculation methods. FER resistance was evaluated at maturity as a percentage of infected kernels on the ears. Fumonisin B1 accumulation in the grains was predicted by NIR spectroscopy. In parallel, a molecular linkage map was constructed for the CO441xCO354 progeny using a Genotyping-by-Sequencing (GBS) approach. GBS provides low cost, high-density information useful to develop highly saturated linkage maps and to add new value to traditional bi-parental mapping and breeding populations. In total 157 F3 DNA pools and the parents were restricted with ApeKI, 96-plex barcoded libraries were constructed according to the Elshire protocol (PLoS ONE 6(5):e19379) and sequenced on an Illumina HiSeq2000 instrument. Initial analyses identified a set of 16.236 SNP markers. Stringent criteria were applied for SNP calling and filtering included a minimum quality score of 20 (Phredscale) for reads bases and a minimum reads mapping quality of 30 (Phred-scale), absence of missing data in the reference samples, less than 30% missing data in the population for each SNP filters on segregation distortion and linkage disequilibrium. Finally a set of 339 SNPs were integrated with genotyping data for 72 SSRs to construct a linkage map. A total of 31 QTLs (four traits in two different years) were detected, using IM and MQM analysis, in five main chromosomal regions

A PM10 chemically characterized nation-wide dataset for Italy. Geographical influence on urban air pollution and source apportionment

Urban textures of the Italian cities are peculiarly shaped by the local geography generating similarities among cities placed in different regions but comparable topographical districts. This suggested the following scientific question: can different topographies generate significant differences on the PM10 chemical composition at Italian urban sites that share similar geography despite being in different regions? To investigate whether such communalities can be found and are applicable at Country-scale, we propose here a novel methodological approach. A dataset comprising season-averages of PM10 mass concentration and chemical composition data was built, covering the decade 2005–2016 and referring to urban sites only (21 cities). Statistical analyses, estimation of missing data, identification of latent clusters and source apportionment modeling by Positive Matrix Factorization (PMF) were performed on this unique dataset. The first original result is the demonstration that a dataset with atypical time resolution can be successfully exploited as an input matrix for PMF obtaining Country-scale representative chemical profiles, whose physical consistency has been assessed by different tests of modeling performance. Secondly, this dataset can be considered a reference repository of season averages of chemical species over the Italian territory and the chemical profiles obtained by PMF for urban Italian agglomerations could contribute to emission repositories. These findings indicate that our approach is powerful, and it could be further employed with datasets typically available in the air pollution monitoring networks

Spatial and seasonal variability of carbonaceous aerosol across Italy

This paper analyses elemental (EC), organic (OC) and total carbon (TC) concentration in PM2.5 and PM10 samples collected over the last few years within several national and European projects at 37 remote, rural, urban, and traffic sites across the Italian peninsula