The Suspended Sediment Flux in Winter in the South of Chengshantou, between the North and South Yellow Sea.

Due to the regional differences between the North and South Yellow Sea, and under the influence of winter winds, the relative changes in the coastal current and the Yellow Sea warm current will lead to the instability of the front, which will lead to the cross-front transport of sediment. Therefore, the study of sediment exchange between the North and South Yellow Sea has become an indispensable part of the study of the Yellow Sea environment. In this study, the current field and sediment concentration in the southern part of Chengshantou, a representative area of the Yellow Sea, were observed in winter in order to analyze the sediment exchange process between the North Yellow Sea and the South Yellow Sea in winter.

A study on optimization of pat gene expression cassette for maize transformation.

Phosphinothricin acetyltransferase gene (pat) is an important selectable marker and also a key herbicide trait gene in several commercial products. In maize, the transformation frequency (TF) using pat as a selectable marker is the lowest among the commonly used marker options including epsps, pmi or ppo. Low pat transformation efficiency can become a major bottleneck in our ability to efficiently produce large numbers of events, especially for large molecular stack vectors with multiple trait gene cassettes.

Evaluation of the utility of gene expression and metabolic information for genomic prediction in maize.

Predictive ability derived from gene expression and metabolic information was evaluated using genomic prediction methods based on datasets from a public maize panel. With the rapid development of high throughput biological technologies, information from gene expression and metabolites has received growing attention in plant genetics and breeding. In this study, we evaluated the utility of gene expression and metabolic information for genomic prediction using data obtained from a maize diversity panel.

[Evaluation indices of greenhouse gas mitigation technologies in cropland ecosystem].

In spite of the increasing studies on greenhouse gas (GHG) emissions mitigation technologies, there is still a lack of systematic indices for evaluation of their overall impacts in croplands. In this study, we collected all the indices relating to greenhouse gas emissions and analyzed each index following the principles of representativeness, objectivity, completeness, dominance and operability. Finally, we proposed evaluation indices for mitigation technologies based on the current situation of China.

The impact of population structure on genomic prediction in stratified populations.

Impacts of population structure on the evaluation of genomic heritability and prediction were investigated and quantified using high-density markers in diverse panels in rice and maize. Population structure is an important factor affecting estimation of genomic heritability and assessment of genomic prediction in stratified populations. In this study, our first objective was to assess effects of population structure on estimations of genomic heritability using the diversity panels in rice and maize.

Family-based association mapping in crop species.

Identification of allelic variants associated with complex traits provides molecular genetic information associated with variability upon which both artificial and natural selections are based. Family-based association mapping (FBAM) takes advantage of linkage disequilibrium among segregating progeny within crosses and among parents to provide greater power than association mapping and greater resolution than linkage mapping. Herein, we discuss the potential adaption of human family-based association tests and quantitative transmission disequilibrium tests for use in crop species.

Accuracy of across-environment genome-wide prediction in maize nested association mapping populations.

Most of previous empirical studies with genome-wide prediction were focused on within-environment prediction based on a single-environment (SE) model. In this study, we evaluated accuracy improvements of across-environment prediction by using genetic and residual covariance across correlated environments. Predictions with a multienvironment (ME) model were evaluated for two corn polygenic leaf structure traits, leaf length and leaf width, based on within-population (WP) and across-population (AP) experiments using a large maize nested association mapping data set consisting of 25 populations of recombinant inbred-lines.

[Distribution characteristics of heavy metals in soil profile of facility vegetable fields].

Taking the facility vegetable fields having been planted for 1-12 years and the adjacent wheat land in Shouguang City of Shandong Province as test objects, this paper studied the distribution characteristics of arsenic (As), cadmium (Cd), copper (Cu), zinc (Zn), chromium (Cr), and nickel (Ni) in their soil profiles (0-150 cm). With the increase of soil depth, the test heavy metals contents in the soil profiles all had a decreasing trend, and in the same soil layers, the contents were obviously higher in facility vegetable fields than in wheat land. Comparing with those in the same soil layers of wheat land, the average contents of As, Cd, Cu, Zn, Cr, and Ni in 0-20 and 120-150 cm soil layers of facility vegetable fields were 35.

Identification of Las2, a major modifier gene affecting the Pas1 mouse lung tumor susceptibility locus.

Lung cancer is the leading cause of cancer death worldwide. Here, we describe a genome-wide association study of chemically induced lung tumorigenesis on 593 mice from 21 inbred strains using 115,904 genotyped and 1,952,918 imputed single nucleotide polymorphisms (SNPs). Using a genetic background-controlled genome search, we identified a novel lung tumor susceptibility gene Las2 (Lung adenoma susceptibility 2) on distal chromosome 18.

Fine mapping of chromosome 6q23-25 region in familial lung cancer families reveals RGS17 as a likely candidate gene.

Purpose: We have previously mapped a major susceptibility locus influencing familial lung cancer risk to chromosome 6q23-25. However, the causal gene at this locus remains undetermined. In this study, we further refined this locus to identify a single candidate gene, by fine mapping using microsatellite markers and association studies using high-density single nucleotide polymorphisms (SNP).

Familial aggregation of common sequence variants on 15q24-25.1 in lung cancer.

Three recent genome-wide association studies identified associations between markers in the chromosomal region 15q24-25.1 and the risk of lung cancer. We conducted a genome-wide association analysis to investigate associations between single-nucleotide polymorphisms (SNPs) and the risk of lung cancer, in which we used blood DNA from 194 case patients with familial lung cancer and 219 cancer-free control subjects.

Common human cancer genes discovered by integrated gene-expression analysis.

Background: Microarray technology enables a standardized, objective assessment of oncological diagnosis and prognosis. However, such studies are typically specific to certain cancer types, and the results have limited use due to inadequate validation in large patient cohorts. Discovery of genes commonly regulated in cancer may have an important implication in understanding the common molecular mechanism of cancer.

Enhanced lung tumor development in tobacco smoke-exposed p53 transgenic and Kras2 heterozygous deficient mice.

A/J mice bearing either a mutation in the p53 gene or a Kras2 heterozygous deficiency were investigated for their susceptibility to tobacco smoke-induced lung tumorigenesis. Transgenic mice and their wild-type littermates were exposed to mainstream tobacco smoke (MS) for 5 mo, followed by 4 mo of recovery in filtered air. In sham (filtered air) groups, p53 transgenic mice did not exhibit a higher tumor multiplicity but did exhibit larger tumors, with tumor load increased 3.

Large-scale in silico mapping of complex quantitative traits in inbred mice.

Understanding the genetic basis of common disease and disease-related quantitative traits will aid in the development of diagnostics and therapeutics. The processs of gene discovery can be sped up by rapid and effective integration of well-defined mouse genome and phenome data resources. We describe here an in silico gene-discovery strategy through genome-wide association (GWA) scans in inbred mice with a wide range of genetic variation.

EGFR-T790M is a rare lung cancer susceptibility allele with enhanced kinase activity.

The use of tyrosine kinase inhibitors (TKI) has yielded great success in treatment of lung adenocarcinomas. However, patients who develop resistance to TKI treatment often acquire a somatic resistance mutation (T790M) located in the catalytic cleft of the epidermal growth factor receptor (EGFR) enzyme. Recently, a report describing EGFR-T790M as a germ-line mutation suggested that this mutation may be associated with inherited susceptibility to lung cancer.

Identification of a novel tumor suppressor gene p34 on human chromosome 6q25.1.

In this study, we observed loss of heterozygosity (LOH) in human chromosomal fragment 6q25.1 in sporadic lung cancer patients. LOH was observed in 65% of the 26 lung tumors examined and was narrowed down to a 2.

Candidate lung tumor susceptibility genes identified through whole-genome association analyses in inbred mice.

We performed a whole-genome association analysis of lung tumor susceptibility using dense SNP maps ( approximately 1 SNP per 20 kb) in inbred mice. We reproduced the pulmonary adenoma susceptibility 1 (Pas1) locus identified in previous linkage studies and further narrowed this quantitative trait locus (QTL) to a region of less than 0.5 Mb in which at least two genes, Kras2 (Kirsten rat sarcoma oncogene 2) and Casc1 (cancer susceptibility candidate 1; also known as Las1), are strong candidates.

Five loci, SLT1 to SLT5, controlling the susceptibility to spontaneously occurring lung cancer in mice.

A series of linkage studies was previously conducted to identify quantitative trait loci associated with chemically induced lung tumors. However, little is known of genetic susceptibility to spontaneously occurring lung tumorigenesis (SLT) in mice. In this study, we did a whole-genome linkage disequilibrium analysis for susceptibility to SLT in mice using approximately 135,900 single-nucleotide polymorphisms (SNPs) from the Roche and Genomic Institute of the Novartis Research Foundation SNP databases.

Pooled analysis of loss of heterozygosity in breast cancer: a genome scan provides comparative evidence for multiple tumor suppressors and identifies novel candidate regions.

Somatic loss of heterozygosity (LOH) has been widely reported in breast cancer as a means of identifying putative tumor-suppressor genes. However, individual studies have rarely spanned more than a single chromosome, and the varying criteria used to declare LOH complicate efforts to formally differentiate regions of consistent versus sporadic (random) loss. We report here the compilation of an extensive database from 151 published LOH studies of breast cancer, with summary data from >15,000 tumors and primary allelotypes from >4,300 tumors.

Nonparametric disequilibrium mapping of functional sites using haplotypes of multiple tightly linked single-nucleotide polymorphism markers.

As the speed and efficiency of genotyping single-nucleotide polymorphisms (SNPs) increase, using the SNP map, it becomes possible to evaluate the extent to which a common haplotype contributes to the risk of disease. In this study we propose a new procedure for mapping functional sites or regions of a candidate gene of interest using multiple linked SNPs. Based on a case-parent trio family design, we use expectation-maximization (EM) algorithm-derived haplotype frequency estimates of multiple tightly linked SNPs from both unambiguous and ambiguous families to construct a contingency statistic S for linkage disequilibrium (LD) analysis.

Linkage disequilibrium mapping of novel lung tumor susceptibility quantitative trait loci in mice.

Linkage disequilibrium (LD) has been used to map chromosomal regions regulating quantitative traits, also called quantitative trait loci (QTLs). With the increasing number of available mouse polymorphic genetic markers, LD can be estimated for the purpose of fine-mapping a given QTL or in the identification of novel QTLs. A whole-genome LD analysis was conducted for mapping mouse lung tumor susceptibility QTLs in 25 strains of mice with known susceptibility to lung cancer using 5638 genetic markers.