The depressions in RBC, WBC, and neutrophils observed in this study are not only exposure dependent, but also significantly different in the lowest exposed group (at or below 0.25 ppm) compared with unexposed subjects. The results of the present study appear to suggest that lymphocytes may not be more sensitive to chronic benzene exposure than neutrophils.

Background The present study was conducted among Chinese workers employed in glue‐ and shoe‐making factories who had an average daily personal benzene exposure of 31±26 ppm (mean±SD). The metabolites monitored were S‐phenylmercapturic acid (S‐PMA), trans, trans‐muconic acid (t,t‐MA), hydroquinone (HQ), catechol (CAT), 1,2,4‐trihydroxybenzene (benzene triol, BT), and phenol. Methods S‐PMA, t,t‐MA, HQ, CAT, and BT were quantified by HPLC‐tandem mass spectrometry. Phenol was measured by GC‐MS. Results Levels of benzene metabolites (except BT) measured in urine samples collected from exposed workers at the end of workshift were significantly higher than those measured in unexposed subjects (P < 0.0001). The large increases in urinary metabolites from before to after work strongly correlated with benzene exposure. Concentrations of these metabolites in urine samples collected from exposed workers before work were also significantly higher than those from unexposed subjects. The half‐lives of S‐PMA, t,t‐MA, HQ, CAT, and phenol were estimated from a time course study to be 12.8, 13.7, 12.7, 15.0, and 16.3 h, respectively. Conclusions All metabolites, except BT, are good markers for benzene exposure at the observed levels; however, due to their high background, HQ, CAT, and phenol may not distinguish unexposed subjects from workers exposed to benzene at low ambient levels. S‐PMA and t,t‐MA are the most sensitive markers for low level benzene exposure. Am. J. Ind. Med. 37:522–531, 2000. © 2000 Wiley‐Liss, Inc.

Roots are complicated quantitative characteristics that play an essential role in absorbing water and nutrients. To uncover the genetic variations for root-related traits in rapeseed, twelve mature root traits of a Brassica napus association panel were investigated in the field within three environments. All traits showed significant phenotypic variation among genotypes, with heritabilities ranging from 55.18% to 79.68%. Genome-wide association studies (GWAS) using 20,131 SNPs discovered 172 marker-trait associations, including 103 significant SNPs (−log10 (p) > 4.30) that explained 5.24–20.31% of the phenotypic variance. With the linkage disequilibrium r2 > 0.2, these significant associations were binned into 40 quantitative trait loci (QTL) clusters. Among them, 14 important QTL clusters were discovered in two environments and/or with phenotypic contributions greater than 10%. By analyzing the genomic regions within 100 kb upstream and downstream of the peak SNPs within the 14 loci, 334 annotated genes were found. Among these, 32 genes were potentially associated with root development according to their expression analysis. Furthermore, the protein interaction network using the 334 annotated genes gave nine genes involved in a substantial number of interactions, including a key gene associated with root development, BnaC09g36350D. This research provides the groundwork for deciphering B. napus’ genetic variations and improving its root system architecture.

Background In terms of global demand, rapeseed is the third-largest oilseed crop after soybeans and palm, which produces vegetable oil for human consumption and biofuel for industrial production. Roots are vital organs for plant to absorb water and attain mineral nutrients, thus they are of great importance to plant productivity. However, the genetic mechanisms regulating root development in rapeseed remain unclear. In the present study, seven root-related traits and shoot biomass traits in 280 Brassica napus accessions at five continuous vegetative stages were measured to establish the genetic basis of root growth in rapeseed. Results The persistent and stage-specific genetic mechanisms were revealed by root dynamic analysis. Sixteen persistent and 32 stage-specific quantitative trait loci (QTL) clusters were identified through genome-wide association study (GWAS). Root samples with contrasting (slow and fast) growth rates throughout the investigated stages and those with obvious stage-specific changes in growth rates were subjected to transcriptome analysis. A total of 367 differentially expressed genes (DEGs) with persistent differential expressions throughout root development were identified, and these DEGs were significantly enriched in GO terms, such as energy metabolism and response to biotic or abiotic stress. Totally, 485 stage-specific DEGs with different expressions at specific stage were identified, and these DEGs were enriched in GO terms, such as nitrogen metabolism. Four candidate genes were identified as key persistent genetic factors and eight as stage-specific ones by integrating GWAS, weighted gene co-expression network analysis (WGCNA), and differential expression analysis. These candidate genes were speculated to regulate root system development, and they were less than 100 kb away from peak SNPs of QTL clusters. The homologs of three genes (BnaA03g52990D, BnaA06g37280D, and BnaA09g07580D) out of 12 candidate genes have been reported to regulate root development in previous studies. Conclusions Sixteen QTL clusters and four candidate genes controlling persistently root development, and 32 QTL clusters and eight candidate genes stage-specifically regulating root growth in rapeseed were detected in this study. Our results provide new insights into the temporal genetic mechanisms of root growth by identifying key candidate QTL/genes in rapeseed.