SummaryThe base‐editing technique using CRISPR/nCas9 (Cas9 nickase) or dCas9 (deactivated Cas9) fused with cytidine deaminase is a powerful tool to create point mutations. In this study, a novel G. hirsutum‐Base Editor 3 (GhBE3) base‐editing system has been developed to create single‐base mutations in the allotetraploid genome of cotton (Gossypium hirsutum). A cytidine deaminase sequence (APOBEC) fused with nCas9 and uracil glycosylase inhibitor (UGI) was inserted into our CRISPR/Cas9 plasmid (pRGEB32‐GhU6.7). Three target sites were chosen for two target genes, GhCLA and GhPEBP, to test the efficiency and accuracy of GhBE3. The editing efficiency ranged from 26.67 to 57.78% at the three target sites. Targeted deep sequencing revealed that the C→T substitution efficiency within an ‘editing window’, approximately six‐nucleotide windows of −17 to −12 bp from the PAM sequence, was up to 18.63% of the total sequences. The 27 most likely off‐target sites predicted by CRISPR‐P and Cas‐OFFinder tools were analysed by targeted deep sequencing, and it was found that rare C→T substitutions (average < 0.1%) were detected in the editing windows of these sites. Furthermore, whole‐genome sequencing analyses on two GhCLA‐edited and one wild‐type plants with about 100× depth showed that no bona fide off‐target mutations were detectable from 1500 predicted potential off‐target sites across the genome. In addition, the edited bases were inherited to T1 progeny. These results demonstrate that GhBE3 has high specificity and accuracy for the generation of targeted point mutations in allotetraploid cotton.

Knowledge of the relative abundance of primary organic aerosol (POA) and secondary organic aerosol (SOA) forms an important scientific basis for formulating particulate matter (PM) control policies. Taking advantage of a comprehensive chemical composition data set of PM2.5 including both POA and SOA tracers (most notably, SOA tracers of a few biogenic voltaic organic compound precursors), we investigate the impact of inclusion of SOA tracers on the source apportionment of organic carbon (OC) and PM2.5 in the Pearl River Delta region of China using positive matrix factorization (PMF). In PMF runs incorporating SOA tracers (PMFw), ten PMF factors were resolved including four secondary factors: (1) SOA I (α-pinene, β-caryophyllene, and naphthalene-derived SOA), (2) SOA II (isoprene-derived SOA), (3) a secondary sulfate factor, and (4) a secondary nitrate factor. In PMF tests without SOA tracers (PMFwo), the SOA I and SOA II factors could not be extracted, but the remaining eight source factors were resolved. Among the eight common source factors, the industrial emission factor, identified by high loadings of Zn and Pb, showed the largest variations between PMFw and PMFwo solutions. The source contributions of SOA I and SOA II resolved in PMFw were largely shifted to the industry emission source in PMFwo. Secondary organic carbon (SOC) summed from the four secondary factors in PMFw contributed ∼40% (4.47 μgC/m3), and the SOC estimate by PMFwo (3.51 μgC/m3) was 21% lower due to the inability to extract SOA I and SOA II. Secondary PM2.5 by PMFwo was 6% lower than that by PMFw (23.7 vs 25.2 μg/m3). The PMFw results indicated that SOC from specific precursors may have different formation pathways than secondary sulfate and nitrate formation processes, and their source contributions could not be properly resolved without the indicative tracers included in PMF. This study demonstrates the utility of biogenic SOA tracers in resolving isoprene-derived SOA and highlights the need for more SOA tracers, especially those specific to anthropogenic precursors, in improving the source apportionment for those broad OA sources such as industrial emissions.

The organic composition of airborne fine particulate matter (PM 2.5 , aerodynamic diameter less than 2.5 μm) at a molecular level has yet to be achieved, hindering a full understanding of the climatic impacts and health effects of PM 2.5 . Compounds containing aromatic rings are closely associated with optically active brown carbon and toxicologically important quinones. In this work, a group of ten aromatic organic acids including three phthalic acids, four phenolic acids, and three benzene-tricarboxylic acids (BTCAs) in PM 2.5 were studied for their abundance and potential sources through quantifying their ambient concentrations at four sites in the Pearl River Delta (PRD) region in Southern China, where biomass burning and anthropogenic emissions are both significant PM sources. Average concentrations of individual aromatic acids in a total of 240 PM 2.5 samples collected throughout 2012 were in the order of 0.1−20 ng/m 3 with p-and o-phthalic acid being the most abundant. Interspecies correlation analysis with known PM source tracers reveals different source origins for the ten aromatic acids. The four phenolic acids, all possessing partial lignin structures, are highly correlated with levoglucosan, indicating their association with biomass burning emissions. Specific lignin tracer ratios characteristic of different types of biomass fuels (i.e., cinnamyl-to vanillyl-phenol ratio) revealed the significant influence of crop burning emissions in the PRD region. The three BTCAs have moderate correlation with sulfate but no correlation with levoglucosan, suggesting a strong association with secondary formation origins while negating a strong link with biomass burning. The three phthalic acids are moderately correlated with sulfate, levoglucosan, and a number of polycyclic aromatic hydrocarbons (PAHs), indicating multiple significant sources. This study provides a valuable data set toward establishing quantitative links between molecular composition of organic matter and the optical and toxicological properties of PM 2.5 as well as assisting identification of tracers for PM 2.5 sources.

BackgroundMillennia of directional human selection has reshaped the genomic architecture of cultivated cotton relative to wild counterparts, but we have limited understanding of the selective retention and fractionation of genomic components.ResultsWe construct a comprehensive genomic variome based on 1961 cottons and identify 456 Mb and 357 Mb of sequence with domestication and improvement selection signals and 162 loci, 84 of which are novel, including 47 loci associated with 16 agronomic traits. Using pan-genome analyses, we identify 32,569 and 8851 non-reference genes lost fromGossypium hirsutumandGossypium barbadensereference genomes respectively, of which 38.2% (39,278) and 14.2% (11,359) of genes exhibit presence/absence variation (PAV). We document the landscape of PAV selection accompanied by asymmetric gene gain and loss and identify 124 PAVs linked to favorable fiber quality and yield loci.ConclusionsThis variation repertoire points to genomic divergence during cotton domestication and improvement, which informs the characterization of favorable gene alleles for improved breeding practice using a pan-genome-based approach.

Molecular markers in ambient organic aerosol (OA) provide highly specific source information. Their traditional quantification is based on offline analysis of filter samples, and the coarse time resolution and labor-intensive nature hugely limit the utility of the tracer data. In this study, hourly organic molecular markers in fine particulate matter were measured using a recently commercialized thermal desorption aerosol gas chromatography− mass spectrometry (TAG) technique at an urban location in Shanghai, China during a three-week campaign from 9 November to 3 December, 2018. Selected primary OA molecular markers, including anhydrosugars, fatty acids, aromatic acids, and polycyclic aromatic hydrocarbons (PAHs), were examined in detail. Their diurnal variations showed characteristic features representing the corresponding emission source activities. For example, stearic acid showed a clear peak around 7 pm, in accordance with the enhanced cooking activities during mealtime. Diagnostic ratios of related makers of different reactivities provided unique information in uncovering the source information and tracking evolution of the OA in the atmosphere, for example, ratios of levoglucosan to its isomers and K + identified crop residue burning as the major form of biomass burning (BB). Ratios of unsaturated and saturated fatty acids gave unambiguous indication of atmospheric degradation of unsaturated fatty acids after emissions. Oleic acid to stearic acid ratios in ambient data (0.83 ± 0.54) were lower than those in the source profiles (1.2−6.5). Furthermore, the oleic acid to stearic acid ratio was found to be highly correlated with O/C ratios (R p : −0.66), suggesting the possible utility of oleic acid as a model compound to examine the heterogeneous reaction of cooking-related OA. PAH ratio−ratio plots helped identify varying influences of major combustion sources associated with air masses of different origins, revealing that BB and coal combustion were dominant under the influence of long-range transport air mass, while vehicle emissions were dominant under local/median-range air mass influence. This study demonstrated the utility of high time-resolution organic markers in capturing the dynamic change of source emissions and atmospheric aging, providing observational evidence to support their use in source apportionment.

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We demonstrate with field data the benefit of using high‐time‐resolution chemical speciation data in achieving more robust source apportionment of fine particulate matter (PM2.5) using positive matrix factorization (PMF). Hourly composition data were collected over a month in Shanghai, including four inorganic ions, 13 elements, organic, and elemental carbon. PMF analysis of the hourly data set (PMF1h) resolves eight factors: secondary nitrate/sulfate, vehicular/industrial emissions, coal combustion, secondary sulfate, tire wear, Cr and Ni point source, residual oil combustion, and dust, with the first three being the major ones and each contributing to >20% of PM2.5 mass. To characterize the benefit gained from time resolution, we carried out separate PMF analyses of 4‐ and 6‐hr averaged data of the same data set (PMF6h and PMF4h). PMF6h and PMF4h produce an eight‐factor solution sharing similar factors to those by PMF1h but show less stability and more mixing in source profiles. Profile mixing was especially noticeable for tire wear, coal combustion, and Cr and Ni point source in PMF6h, as the 6‐hr averaging significantly decreased between‐sample variability and increased rotational ambiguity. While the three sets of PMF solutions were similar in contributions for factors with major species as source markers (e.g., secondary nitrate/sulfate), larger variations existed for factors with trace species as markers due to mixing of major species in the profiles and higher rotational uncertainties in PMF4h and PMF6h. Our results indicate that hourly time series of elements and major components could achieve more robust source apportionment through better capturing of diurnal‐scale dynamics in source activities.

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