The role of TGF-β-induced epithelial-mesenchymal transition (EMT) in cancer cell dissemination is well established, but the involvement of lncRNAs in TGF-β signaling is still unknown. In this study, we observed that the lncRNA-activated by TGF-β (lncRNA-ATB) was upregulated in hepatocellular carcinoma (HCC) metastases and associated with poor prognosis. lncRNA-ATB upregulated ZEB1 and ZEB2 by competitively binding the miR-200 family and then induced EMT and invasion. In addition, lncRNA-ATB promoted organ colonization of disseminated tumor cells by binding IL-11 mRNA, autocrine induction of IL-11, and triggering STAT3 signaling. Globally, lncRNA-ATB promotes the invasion-metastasis cascade. Thus, these findings suggest that lncRNA-ATB, a mediator of TGF-β signaling, could predispose HCC patients to metastases and may serve as a potential target for antimetastatic therapies.

Maize kernel oil is a valuable source of nutrition. Here we extensively examine the genetic architecture of maize oil biosynthesis in a genome-wide association study using 1.03 million SNPs characterized in 368 maize inbred lines, including 'high-oil' lines. We identified 74 loci significantly associated with kernel oil concentration and fatty acid composition (P < 1.8 × 10(-6)), which we subsequently examined using expression quantitative trait loci (QTL) mapping, linkage mapping and coexpression analysis. More than half of the identified loci localized in mapped QTL intervals, and one-third of the candidate genes were annotated as enzymes in the oil metabolic pathway. The 26 loci associated with oil concentration could explain up to 83% of the phenotypic variation using a simple additive model. Our results provide insights into the genetic basis of oil biosynthesis in maize kernels and may facilitate marker-based breeding for oil quantity and quality.

Many protein-coding oncofetal genes are highly expressed in murine and human fetal liver and silenced in adult liver. The protein products of these hepatic oncofetal genes have been used as clinical markers for the recurrence of hepatocellular carcinoma (HCC) and as therapeutic targets for HCC. Herein we examined the expression profiles of long noncoding RNAs (lncRNAs) found in fetal and adult liver in mice. Many fetal hepatic lncRNAs were identified; one of these, lncRNA-mPvt1, is an oncofetal RNA that was found to promote cell proliferation, cell cycling, and the expression of stem cell-like properties of murine cells. Interestingly, we found that human lncRNA-hPVT1 was upregulated in HCC tissues and that patients with higher lncRNA-hPVT1 expression had a poor clinical prognosis. The protumorigenic effects of lncRNA-hPVT1 on cell proliferation, cell cycling, and stem cell-like properties of HCC cells were confirmed both in vitro and in vivo by gain-of-function and loss-of-function experiments. Moreover, mRNA expression profile data showed that lncRNA-hPVT1 up-regulated a series of cell cycle genes in SMMC-7721 cells. By RNA pulldown and mass spectrum experiments, we identified NOP2 as an RNA-binding protein that binds to lncRNA-hPVT1. We confirmed that lncRNA-hPVT1 up-regulated NOP2 by enhancing the stability of NOP2 proteins and that lncRNA-hPVT1 function depends on the presence of NOP2. Conclusion: Our study demonstrates that the expression of many lncRNAs is up-regulated in early liver development and that the fetal liver can be used to search for new diagnostic markers for HCC. LncRNA-hPVT1 promotes cell proliferation, cell cycling, and the acquisition of stem cell-like properties in HCC cells by stabilizing NOP2 protein. Regulation of the lncRNA-hPVT1/NOP2 pathway may have beneficial effects on the treatment of HCC. (HEPATOLOGY 2014;60:1278-1290

The postdomestication adaptation of maize to longer days required reduced photoperiod sensitivity to optimize flowering time. We performed a genome-wide association study and confirmed that ZmCCT, encoding a CCT domain-containing protein, is associated with the photoperiod response. In early-flowering maize we detected a CACTA-like transposable element (TE) within the ZmCCT promoter that dramatically reduced flowering time. TE insertion likely occurred after domestication and was selected as maize adapted to temperate zones. This process resulted in a strong selective sweep within the TE-related block of linkage disequilibrium. Functional validations indicated that the TE represses ZmCCT expression to reduce photoperiod sensitivity, thus accelerating maize spread to long-day environments.

Association mapping is a powerful approach for dissecting the genetic architecture of complex quantitative traits using high-density SNP markers in maize. Here, we expanded our association panel size from 368 to 513 inbred lines with 0.5 million high quality SNPs using a two-step data-imputation method which combines identity by descent (IBD) based projection and k-nearest neighbor (KNN) algorithm. Genome-wide association studies (GWAS) were carried out for 17 agronomic traits with a panel of 513 inbred lines applying both mixed linear model (MLM) and a new method, the Anderson-Darling (A-D) test. Ten loci for five traits were identified using the MLM method at the Bonferroni-corrected threshold −log10 (P) >5.74 (α = 1). Many loci ranging from one to 34 loci (107 loci for plant height) were identified for 17 traits using the A-D test at the Bonferroni-corrected threshold −log10 (P) >7.05 (α = 0.05) using 556809 SNPs. Many known loci and new candidate loci were only observed by the A-D test, a few of which were also detected in independent linkage analysis. This study indicates that combining IBD based projection and KNN algorithm is an efficient imputation method for inferring large missing genotype segments. In addition, we showed that the A-D test is a useful complement for GWAS analysis of complex quantitative traits. Especially for traits with abnormal phenotype distribution, controlled by moderate effect loci or rare variations, the A-D test balances false positives and statistical power. The candidate SNPs and associated genes also provide a rich resource for maize genetics and breeding.

Deciphering the influence of genetics on primary metabolism in plants will provide insights useful for genetic improvement and enhance our fundamental understanding of plant growth and development. Although maize (Zea mays) is a major crop for food and feed worldwide, the genetic architecture of its primary metabolism is largely unknown. Here, we use high-density linkage mapping to dissect large-scale metabolic traits measured in three different tissues (leaf at seedling stage, leaf at reproductive stage, and kernel at 15 d after pollination [DAP]) of a maize recombinant inbred line population. We identify 297 quantitative trait loci (QTLs) with moderate (86.2% of the mapped QTL, R 2 = 2.4 to 15%) to major effects (13.8% of the mapped QTL, R 2 >15%) for 79 primary metabolites across three tissues. Pairwise epistatic interactions between these identified loci are detected for more than 25.9% metabolites explaining 6.6% of the phenotypic variance on average (ranging between 1.7 and 16.6%), which implies that epistasis may play an important role for some metabolites. Key candidate genes are highlighted and mapped to carbohydrate metabolism, the tricarboxylic acid cycle, and several important amino acid biosynthetic and catabolic pathways, with two of them being further validated using candidate gene association and expression profiling analysis. Our results reveal a metabolite-metabolite-agronomic trait network that, together with the genetic determinants of maize primary metabolism identified herein, promotes efficient utilization of metabolites in maize improvement.

We thank J. Li from the China Agricultural University for providing the seeds of SK, X. Li for helping to conduct ChIA-PET sequencing and K. Kremling for critical comments on the manuscript.

SummaryImprovement of grain yield is an essential long-term goal of maize (Zea mays) breeding to meet continual and increasing food demands worldwide, but the genetic basis remains unclear.We used 10 different recombination inbred line (RIL) populations genotyped with highdensity markers and phenotyped in multiple environments to dissect the genetic architecture of maize ear traits.Three methods were used to map the quantitative trait loci (QTLs) affecting ear traits. We found 17-34 minor-or moderate-effect loci that influence ear traits, with little epistasis and environmental interactions, totally accounting for 55.4-82% of the phenotypic variation. Four novel QTLs were validated and fine mapped using candidate gene association analysis, expression QTL analysis and heterogeneous inbred family validation.The combination of multiple different populations is a flexible and manageable way to collaboratively integrate widely available genetic resources, thereby boosting the statistical power of QTL discovery for important traits in agricultural crops, ultimately facilitating breeding programs.