Recent research has identified critical roles for microRNAs in a large number of cellular processes, including tumorigenic transformation. While significant progress has been made towards understanding the mechanisms of gene regulation by microRNAs, much less is known about factors affecting the expression of these noncoding transcripts. Here, we demonstrate for the first time a functional link between hypoxia, a welldocumented tumor microenvironment factor, and microRNA expression. Microarray-based expression profiles revealed that a specific spectrum of microRNAs (including miR-23, -24, -26, -27, -103, -107, -181, -210, and -213) is induced in response to low oxygen, at least some via a hypoxia-inducible-factor-dependent mechanism. Select members of this group (miR-26, -107, and -210) decrease proapoptotic signaling in a hypoxic environment, suggesting an impact of these transcripts on tumor formation. Interestingly, the vast majority of hypoxiainduced microRNAs are also overexpressed in a variety of human tumors.

Increasing food production is essential to meet the demands of a growing human population, with its rising income levels and nutritional expectations. To address the demand, plant breeders seek new sources of genetic variation to enhance the productivity, sustainability and resilience of crop varieties. Here we launch a high-resolution, open-access research platform to facilitate genome-wide association mapping in rice, a staple food crop. The platform provides an immortal collection of diverse germplasm, a high-density single-nucleotide polymorphism data set tailored for gene discovery, well-documented analytical strategies, and a suite of bioinformatics resources to facilitate biological interpretation. Using grain length, we demonstrate the power and resolution of our new high-density rice array, the accompanying genotypic data set, and an expanded diversity panel for detecting major and minor effect QTLs and subpopulation-specific alleles, with immediate implications for rice improvement.

An open question in the history of human migration is the identity of the earliest Eurasian populations that have left contemporary descendants. The Arabian Peninsula was the initial site of the out-of-Africa migrations that occurred between 125,000 and 60,000 yr ago, leading to the hypothesis that the first Eurasian populations were established on the Peninsula and that contemporary indigenous Arabs are direct descendants of these ancient peoples. To assess this hypothesis, we sequenced the entire genomes of 104 unrelated natives of the Arabian Peninsula at high coverage, including 56 of indigenous Arab ancestry. The indigenous Arab genomes defined a cluster distinct from other ancestral groups, and these genomes showed clear hallmarks of an ancient out-of-Africa bottleneck. Similar to other Middle Eastern populations, the indigenous Arabs had higher levels of Neanderthal admixture compared to Africans but had lower levels than Europeans and Asians. These levels of Neanderthal admixture are consistent with an early divergence of Arab ancestors after the out-of-Africa bottleneck but before the major Neanderthal admixture events in Europe and other regions of Eurasia. When compared to worldwide populations sampled in the 1000 Genomes Project, although the indigenous Arabs had a signal of admixture with Europeans, they clustered in a basal, outgroup position to all 1000 Genomes non-Africans when considering pairwise similarity across the entire genome. These results place indigenous Arabs as the most distant relatives of all other contemporary non-Africans and identify these people as direct descendants of the first Eurasian populations established by the out-of-Africa migrations.

As sequencing and genotyping technologies evolve, crop genetics researchers accumulate increasing numbers of genomic data sets from various genotyping platforms on different germplasm panels. Imputation is an effective approach to increase marker density of existing data sets toward the goal of integrating resources for downstream applications. While a number of imputation software packages are available, the limitations to utilization for the rice community include high computational demand and lack of a reference panel. To address these challenges, we develop the Rice Imputation Server, a publicly available web application leveraging genetic information from a globally diverse rice reference panel assembled here. This resource allows researchers to benefit from increased marker density without needing to perform imputation on their own machines. We demonstrate improvements that imputed data provide to rice genome-wide association (GWA) results of grain amylose content and show that the major functional nucleotide polymorphism is tagged only in the imputed data set.

Background: The TGF-β/SMAD pathway is part of a broader signaling network in which crosstalk between pathways occurs. While the molecular mechanisms of TGF-β/SMAD signaling pathway have been studied in detail, the global networks downstream of SMAD remain largely unknown. The regulatory effect of SMAD complex likely depends on transcriptional modules, in which the SMAD binding elements and partner transcription factor binding sites (SMAD modules) are present in specific context.

Genome-wide association studies (GWAS) and candidate gene studies have identified a number of risk loci associated with the smoking-related disease COPD, a disorder that originates in the airway epithelium. Since airway basal cell (BC) stem/progenitor cells exhibit the earliest abnormalities associated with smoking (hyperplasia, squamous metaplasia), we hypothesized that smoker BC have a dysregulated transcriptome, enriched, in part, at known GWAS/candidate gene loci. Massive parallel RNA sequencing was used to compare the transcriptome of BC purified from the airway epithelium of healthy nonsmokers (n = 10) and healthy smokers (n = 7). The chromosomal location of the differentially expressed genes was compared to loci identified by GWAS to confer risk for COPD. Smoker BC have 676 genes differentially expressed compared to nonsmoker BC, dominated by smoking up-regulation. Strikingly, 166 (25%) of these genes are located on chromosome 19, with 13 localized to 19q13.2 (p<10−4 compared to chance), including 4 genes (NFKBIB, LTBP4, EGLN2 and TGFB1) associated with risk for COPD. These observations provide the first direct connection between known genetic risks for smoking-related lung disease and airway BC, the population of lung cells that undergo the earliest changes associated with smoking.

Exome sequencing of families of related individuals has been highly successful in identifying genetic polymorphisms responsible for Mendelian disorders. Here, we demonstrate the value of the reverse approach, where we use exome sequencing of a sample of unrelated individuals to analyze allele frequencies of known causal mutations for Mendelian diseases. We sequenced the exomes of 100 individuals representing the three major genetic subgroups of the Qatari population (Q1 Bedouin, Q2 Persian-South Asian, Q3 African) and identified 37 variants in 33 genes with effects on 36 clinically significant Mendelian diseases. These include variants not present in 1000 Genomes and variants at high frequency when compared to 1000 Genomes populations. Several of these Mendelian variants were only segregating in one Qatari subpopulation, where the observed subpopulation specificity trends were confirmed in an independent population of 386 Qataris. Pre-marital genetic screening in Qatar tests for only 4 out of the 37, such that this study provides a set of Mendelian disease variants with potential impact on the epidemiological profile of the population that could be incorporated into the testing program if further experimental and clinical characterization confirms high penetrance.

Background: The canonical core promoter elements consist of the TATA box, initiator (Inr), downstream core promoter element (DPE), TFIIB recognition element (BRE) and the newlydiscovered motif 10 element (MTE). The motifs for these core promoter elements are highly degenerate, which tends to lead to a high false discovery rate when attempting to detect them in promoter sequences.