Species identification of oaks (Quercus) is always a challenge because many species exhibit variable phenotypes that overlap with other species. Oaks are notorious for interspecific hybridization and introgression, and complex speciation patterns involving incomplete lineage sorting. Therefore, accurately identifying Quercus species barcodes has been unsuccessful. In this study, we used chloroplast genome sequence data to identify molecular markers for oak species identification. Using next generation sequencing methods, we sequenced 14 chloroplast genomes of Quercus species in this study and added 10 additional chloroplast genome sequences from GenBank to develop a DNA barcode for oaks. Chloroplast genome sequence divergence was low. We identified four mutation hotspots as candidate Quercus DNA barcodes; two intergenic regions (matK-trnK-rps16 and trnR-atpA) were located in the large single copy region, and two coding regions (ndhF and ycf1b) were located in the small single copy region. The standard plant DNA barcode (rbcL and matK) had lower variability than that of the newly identified markers. Our data provide complete chloroplast genome sequences that improve the phylogenetic resolution and species level discrimination of Quercus. This study demonstrates that the complete chloroplast genome can substantially increase species discriminatory power and resolve phylogenetic relationships in plants.

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We used fresh leaves of Sophora japonica L. variety ‘Qingyun 1’ (A0) and 10 superior clones of the same species (A1–A10) to explore leaf morphological characteristics and total particle retention per unit leaf area under natural and artificial simulated dust deposition treatments. Our objectives were to explore the relationship between the two methods and to assess particle size distribution, X-ray fluorescence (XRF) heavy metal content, and scanning electron and atomic force microscopy (SEM and AFM) characteristics of leaf surface microstructure. Using the membership function method, we evaluated the dust retention capacity of each clone based on the mean degree of membership of its dust retention index. Using correlation analysis, we selected leaf morphological and SEM and AFM indices related significantly to dust retention capacity. Sophora japonica showed excellent overall dust retention capacity, although this capacity differed among clones. A5 had the strongest overall retention capacity, A2 had the strongest retention capacity for PM2.5, A9 had the strongest retention capacity for PM2.5–10, A0 had the strongest retention capacity for PM>10, and A2 had the strongest specific surface area (SSA) and heavy metal adsorption capacity. Overall, A1 had the strongest comprehensive dust retention ability, A5 was intermediate, and A7 had the weakest capacity. Certain leaf morphological and SEM and AFM characteristic indices correlated significantly with the dust retention capacity.

Quercus variabilis plays a key role in soil remediation, erosion control, and in the economic and ecosystemic development in eastern Asia. In this study, we sequenced the complete chloroplast genome of Q. variabilis based on next-generation sequencing and used these data to assess genomic resources. The size of the Q. variabilis chloroplast genome is 161,168 bp, including a large single-copy region (90,464 bp), a small single-copy region (19,070 bp), and a pair of inverted repeats regions (25,817 bp). The overall GC content of the Q. acutissima chloroplast genome was 35.7%. The chloroplast genome of Q. variabilis encodes 112 different genes, including 78 protein-coding genes, 30 transfer RNAs (tRNA) and four ribosomal RNAs (rRNA). A phylogenetic tree constructed based on complete chloroplast genome sequences of 15 Quercus species showed that Q. variabilis was sister to Q. acutissima.