To identify genetic susceptibility loci for hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) in the Chinese population, we carried out a genome-wide association study (GWAS) in 2,514 chronic HBV carriers (1,161 HCC cases and 1,353 controls) followed by a 2-stage validation among 6 independent populations of chronic HBV carriers (4,319 cases and 4,966 controls). The joint analyses showed that HCC risk was significantly associated with two independent loci: rs7574865 at STAT4, Pmeta = 2.48 × 10−10, odds ratio (OR) = 1.21; and rs9275319 at HLA-DQ, Pmeta = 2.72 × 10−17, OR = 1.49. The risk allele G at rs7574865 was significantly associated with lower mRNA levels of STAT4 in both the HCC tissues and nontumor tissues of 155 individuals with HBV-related HCC (Ptrend = 0.0008 and 0.0002, respectively). We also found significantly lower mRNA expression of STAT4 in HCC tumor tissues compared with paired adjacent nontumor tissues (P = 2.33 × 10−14).

Grain chalkiness is a highly undesirable quality trait in the marketing and consumption of rice grain. However, the molecular basis of this trait is poorly understood. Here we show that a major quantitative trait locus (QTL), Chalk5, influences grain chalkiness, which also affects head rice yield and many other quality traits. Chalk5 encodes a vacuolar H(+)-translocating pyrophosphatase (V-PPase) with inorganic pyrophosphate (PPi) hydrolysis and H(+)-translocation activity. Elevated expression of Chalk5 increases the chalkiness of the endosperm, putatively by disturbing the pH homeostasis of the endomembrane trafficking system in developing seeds, which affects the biogenesis of protein bodies and is coupled with a great increase in small vesicle-like structures, thus forming air spaces among endosperm storage substances and resulting in chalky grain. Our results indicate that two consensus nucleotide polymorphisms in the Chalk5 promoter in rice varieties might partly account for the differences in Chalk5 mRNA levels that contribute to natural variation in grain chalkiness.

Grains from cereals contribute an important source of protein to human food, and grain protein content (GPC) is an important determinant of nutritional quality in cereals. Here we show that the quantitative trait locus (QTL) qPC1 in rice controls GPC by regulating the synthesis and accumulation of glutelins, prolamins, globulins, albumins and starch. qPC1 encodes a putative amino acid transporter OsAAP6, which functions as a positive regulator of GPC in rice, such that higher expression of OsAAP6 is correlated with higher GPC. OsAAP6 greatly enhances root absorption of a range of amino acids and has effects on the distribution of various amino acids. Two common variations in the potential cis-regulatory elements of the OsAAP6 5′-untranslated region seem to be associated with GPC diversity mainly in indica cultivars. Our results represent the first step toward unravelling the mechanism of regulation underlying natural variation of GPC in rice.

SUMMARYFlowering time is one of the major adaptive traits in domestication of maize and an important selection criterion in breeding. To detect more maize flowering time variants we evaluated flowering time traits using an extremely large multi-genetic background population that contained more than 8000 lines under multiple Sino-United States environments. The population included two nested association mapping (NAM) panels and a natural association panel. Nearly 1 million single-nucleotide polymorphisms (SNPs) were used in the analyses. Through the parallel linkage analysis of the two NAM panels, both common and unique flowering time regions were detected. Genome wide, a total of 90 flowering time regions were identified. One-third of these regions were connected to traits associated with the environmental sensitivity of maize flowering time. The genome-wide association study of the three panels identified nearly 1000 flowering time-associated SNPs, mainly distributed around 220 candidate genes (within a distance of 1 Mb). Interestingly, two types of regions were significantly enriched for these associated SNPs -one was the candidate gene regions and the other was the approximately 5 kb regions away from the candidate genes. Moreover, the associated SNPs exhibited high accuracy for predicting flowering time.

Huangzaosi, Qi319, and Ye478 are foundation inbred lines widely used in maize breeding in China. To elucidate genetic base of yield components and kernel-related traits in these elite lines, two F(2:3) populations derived from crosses Qi319 × Huangzaosi (Q/H, 230 families) and Ye478 × Huangzaosi (Y/H, 235 families), as well as their parents were evaluated in six environments including Henan, Beijing, and Xinjiang in 2007 and 2008. Correlation and hypergeometric probability function analyses showed the dependence of yield components on kernel-related traits. Three mapping procedures were used to identify quantitative trait loci (QTL) for each population: (1) analysis for each of the six environments, (2) joint analysis for each of the three locations across 2 years, and (3) joint analysis across all environments. For the eight traits measured, 90, 89, and 58 QTL for Q/H, and 72, 76, and 51 QTL for Y/H were detected by the three QTL mapping procedures, respectively. About 70% of the QTL from Q/H and 90% of the QTL from Y/H did not show significant QTL × environment interactions in the joint analysis across all environments. Most of the QTL for kernel traits exhibited high stability across 2 years at the same location, even across different locations. Seven major QTL detected under at least four environments were identified on chromosomes 1, 4, 6, 7, 9, and 10 in the populations. Moreover, QTL on chr. 1, chr. 4, and chr. 9 were detected in both populations. These chromosomal regions could be targets for marker-assisted selection, fine mapping, and map-based cloning in maize.

MicroRNAs (miRNAs) are small non-coding RNA molecules, which participate in diverse biological processes and may regulate tumor suppressor genes or oncogenes. Single nucleotide polymorphisms (SNPs) in miRNA may contribute to diverse functional consequences, including cancer development, by altering miRNA expression. Numerous studies have shown the association between miRNA SNPs and cancer risk; however, the results are generally debatable and inconclusive, mainly due to limited statistical power. To assess the relationship between the five most common SNPs (miR-146a rs2910164, miR-196a2 rs11614913, miR-499 rs3746444, miR-149 rs2292832, and miR-27a rs895919) and the risk cancer development, we performed a meta-analysis of 66 published case-control studies. Crude odds ratios at 95% confidence intervals were used to investigate the strength of the association. No association was observed between rs2910164 and cancer risk in the overall group. However, in stratified analysis, we found that either the rs2910164 C allele or the CC genotype was protective against bladder cancer, prostate cancer, cervical cancer, and colorectal cancer, whereas it was a risk factor for papillary thyroid carcinoma and squamous cell carcinoma of the head and neck (SCCHN). Further, rs11614913 was found to be significantly associated with decreased cancer risk, in particular, for bladder cancer, gastric cancer, and SCCHN. For miR-499, a significant association was found between the rs3746444 polymorphism and cancer risk in pooled analysis. In subgroup analysis, similar results were mainly observed for breast cancer. Finally, no association was found between rs2292832 and rs895919 polymorphisms and cancer risk in the overall group and in stratified analysis. In summary, miR-196a2 rs11614913, miR-146a rs2910164, and miR-499 rs3746444 are risk factors for cancer development, whereas mir-149 rs2292832 and miR-27a rs895919 are not associated with cancer risk.

The expression profiles of microRNAs (miRNAs) are associated with the initiation and progression of human tumors. DNA microarrays are widely used to explore the expression patterns of miRNAs. Because of the limited sample size and experimental expense, the statistical power of individual research projects is not sufficient to yield a robust conclusion. However, collected microarray datasets of expression profiles provide opportunities to compile the information of individual studies. Our study carried out a comprehensive meta-analysis of miRNA expression microarray datasets from 28 published tumor studies; it comprises 33 comparisons and nearly 4,000 tumor and corresponding nontumorous samples. This work reports 52 miRNAs as common signatures that are dysregulated in tumors. In addition to the commonly altered miRNAs, five solid cancers displayed specific tissue patterns of altered miRNAs as well. The meta-analysis also revealed some novel tumorrelated miRNAs such as hsa-miR-144, hsa-miR-130b, hsa-miR-132, hsa-miR-154, hsa-miR-192 and hsa-miR-345. We further validated the expression pattern of hsa-miR-154 in human hepatocellular carcinoma by RT-PCR. Restoration of intracellular miR-154 inhibited tumor cell malignance and the G 1 /S transition in cancer cells. Both bioinformatic prediction and western blotting demonstrated that miR-154 could target CCND2. In addition, expression patterns of miR-154 were inversely correlated with those of CCND2 in hepatocellular carcinoma. Overall, this study used a large-scale data analysis to identify a qualified list of miRNAs that are consistently changed in tumors, which could lead to a better understanding of human tumor etiology.

Aberrant N6-methyladenosine (m6A) modification has emerged as a driver of tumor initiation and progression, yet how long noncoding RNAs (lncRNA) are involved in the regulation of m6A remains unknown. Here we utilize data from 12 cancer types from The Cancer Genome Atlas to comprehensively map lncRNAs that are potentially deregulated by DNA methylation. A novel DNA methylation–deregulated and RNA m6A reader–cooperating lncRNA (DMDRMR) facilitated tumor growth and metastasis in clear cell renal cell carcinoma (ccRCC). Mechanistically, DMDRMR bound insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3) to stabilize target genes, including the cell-cycle kinase CDK4 and three extracellular matrix components (COL6A1, LAMA5, and FN1), by specifically enhancing IGF2BP3 activity on them in an m6A-dependent manner. Consequently, DMDRMR and IGF2BP3 enhanced the G1–S transition, thus promoting cell proliferation in ccRCC. In patients with ccRCC, high coexpression of DMDRMR and IGF2BP3 was associated with poor outcomes. Our findings reveal that DMDRMR cooperates with IGF2BP3 to regulate target genes in an m6A-dependent manner and may represent a potential diagnostic, prognostic, and therapeutic target in ccRCC. Significance: This study demonstrates that the lncRNA DMDRMR acts as a cofactor for IGF2BP3 to stabilize target genes in an m6A-dependent manner, thus exerting essential oncogenic roles in ccRCC.