Genome-wide mutagenesis of Zea mays L. using RescueMu transposons

Derived from the maize Mu1 transposon, RescueMu provides strategies for maize gene discovery and mutant phenotypic analysis. 9.92 Mb of gene-enriched sequences next to RescueMu insertion sites were co-assembled with expressed sequence tags and analyzed. Multiple plasmid recoveries identified probable germinal insertions and screening of RescueMu plasmid libraries identified plants containing probable germinal insertions. Although frequently recovered parental insertions and insertion hotspots reduce the efficiency of gene discovery per plasmid, RescueMu targets a large variety of genes and produces knockout mutants

Transcriptome and regulatory maps of decidua-derived stromal cells inform gene discovery in preterm birth

While a genetic component of preterm birth (PTB) has long been recognized and recently mapped by genome-wide association studies (GWASs), the molecular determinants underlying PTB remain elusive. This stems in part from an incomplete availability of functional genomic annotations in human cell types relevant to pregnancy and PTB. We generated transcriptome (RNA-seq), epigenome (ChlP-seq of H3K27ac, H3K4mel, and H3K4me3 histone modifications), open chromatin (ATAC-seq), and chromatin interaction (promoter capture Hi-C) annotations of cultured primary decidua-derived mesenchymal stromal/stem cells and in vitro differentiated decidual stromal cells and developed a computational framework to integrate these functional annotations with results from a GWAS of gestational duration in 56,384 women. Using these resources, we uncovered additional loci associated with gestational duration and target genes of associated loci. Our strategy illustrates how functional annotations in pregnancy-relevant cell types aid in the experimental follow-up of GWAS for PTB and, likely, other pregnancy-related conditions.Peer reviewe

Identification of novel post-transcriptional features in olfactory receptor family mRNAs.

Olfactory receptor (Olfr) genes comprise the largest gene family in mice. Despite their importance in olfaction, how most Olfr mRNAs are regulated remains unexplored. Using RNA-seq analysis coupled with analysis of pre-existing databases, we found that Olfr mRNAs have several atypical features suggesting that post-transcriptional regulation impacts their expression. First, Olfr mRNAs, as a group, have dramatically higher average AU-content and lower predicted secondary structure than do control mRNAs. Second, Olfr mRNAs have a higher density of AU-rich elements (AREs) in their 3'UTR and upstream open reading frames (uORFs) in their 5 UTR than do control mRNAs. Third, Olfr mRNAs have shorter 3' UTR regions and with fewer predicted miRNA-binding sites. All of these novel properties correlated with higher Olfr expression. We also identified striking differences in the post-transcriptional features of the mRNAs from the two major classes of Olfr genes, a finding consistent with their independent evolutionary origin. Together, our results suggest that the Olfr gene family has encountered unusual selective forces in neural cells that have driven them to acquire unique post-transcriptional regulatory features. In support of this possibility, we found that while Olfr mRNAs are degraded by a deadenylation-dependent mechanism, they are largely protected from this decay in neural lineage cells

Analysis of Antisense Expression by Whole Genome Tiling Microarrays and siRNAs Suggests Mis-Annotation of Arabidopsis Orphan Protein-Coding Genes

MicroRNAs (miRNAs) and trans-acting small-interfering RNAs (tasi-RNAs) are small (20-22 nt long) RNAs (smRNAs) generated from hairpin secondary structures or antisense transcripts, respectively, that regulate gene expression by Watson-Crick pairing to a target mRNA and altering expression by mechanisms related to RNA interference. The high sequence homology of plant miRNAs to their targets has been the mainstay of miRNA prediction algorithms, which are limited in their predictive power for other kingdoms because miRNA complementarity is less conserved yet transitive processes (production of antisense smRNAs) are active in eukaryotes. We hypothesize that antisense transcription and associated smRNAs are biomarkers which can be computationally modeled for gene discovery.We explored rice (Oryza sativa) sense and antisense gene expression in publicly available whole genome tiling array transcriptome data and sequenced smRNA libraries (as well as C. elegans) and found evidence of transitivity of MIRNA genes similar to that found in Arabidopsis. Statistical analysis of antisense transcript abundances, presence of antisense ESTs, and association with smRNAs suggests several hundred Arabidopsis 'orphan' hypothetical genes are non-coding RNAs. Consistent with this hypothesis, we found novel Arabidopsis homologues of some MIRNA genes on the antisense strand of previously annotated protein-coding genes. A Support Vector Machine (SVM) was applied using thermodynamic energy of binding plus novel expression features of sense/antisense transcription topology and siRNA abundances to build a prediction model of miRNA targets. The SVM when trained on targets could predict the "ancient" (deeply conserved) class of validated Arabidopsis MIRNA genes with an accuracy of 84%, and 76% for "new" rapidly-evolving MIRNA genes.Antisense and smRNA expression features and computational methods may identify novel MIRNA genes and other non-coding RNAs in plants and potentially other kingdoms, which can provide insight into antisense transcription, miRNA evolution, and post-transcriptional gene regulation

Development and Application of Comparative Gene Co-expression Network Methods in Brachypodium distachyon

Gene discovery and characterization is a long and labor-intensive process. Gene co-expression network analysis is a long-standing powerful approach that can strongly enrich signals within gene expression datasets to predict genes critical for many cellular functions. Leveraging this approach with a large number of transcriptome datasets does not yield a concomitant increase in network granularity. Independently generated datasets that describe gene expression in various tissues, developmental stages, times of day, and environments can carry conflicting co-expression signals. The gene expression responses of the model C3 grass Brachypodium distachyon to abiotic stress is characterized by a co-expression-based analysis, identifying 22 modules of genes, annotated with putative DNA regulatory elements and functional terms. A great deal of co-expression elasticity is found among the genes characterized therein. An algorithm, dGCNA, designed to determine statistically significant changes in gene-gene co-expression relationships is presented. The algorithm is demonstrated on the very well-characterized circadian system of Arabidopsis thaliana, and identifies potential strong signals of molecular interactions between a specific transcription factor and putative target gene loci. Lastly, this network comparison approach based on edge-wise similarities is demonstrated on many pairwise comparisons of independent microarray datasets, to demonstrate the utility of fine-grained network comparison, rather than amassing as large a dataset as possible. This approach identifies a set of 182 gene loci which are differentially expressed under drought stress, change their co-expression strongly under loss of thermocycles or high-salinity stress, and are associated with cell-cycle and DNA replication functions. This set of genes provides excellent candidates for the generation of rhythmic growth under thermocycles in Brachypodium distachyon

Isolation and characterization of developmentally regulated novel target site from embryonic chick heart

Differential gene expression is the primary determinant of numerous biological processes such as cell differentiation, proliferation, organogenesis, tumor progression and apoptosis. In that context, regulatory proteins play pivotal roles and determine cell fate in all physiological conditions of differentiation, development and disease. As these regulatory proteins are present in extremely small amount in cells, their isolation and identification from tissues is impracticable. These regulatory proteins bind to the target sites (DNA elements) located in the promoter, enhancer and other regulatoryregion of the genome. These target sites control the developmental expression of genes. In the present paper we have isolated and characterized one novel target site (GTGTT) which is developmentally expressed during chick heart development

Peanut gene expression profiling in developing seeds at different reproduction stages during Aspergillus parasiticus infection

<p>Abstract</p> <p>Background</p> <p>Peanut (<it>Arachis hypogaea </it>L.) is an important crop economically and nutritionally, and is one of the most susceptible host crops to colonization of <it>Aspergillus parasiticus </it>and subsequent aflatoxin contamination. Knowledge from molecular genetic studies could help to devise strategies in alleviating this problem; however, few peanut DNA sequences are available in the public database. In order to understand the molecular basis of host resistance to aflatoxin contamination, a large-scale project was conducted to generate expressed sequence tags (ESTs) from developing seeds to identify resistance-related genes involved in defense response against <it>Aspergillus </it>infection and subsequent aflatoxin contamination.</p> <p>Results</p> <p>We constructed six different cDNA libraries derived from developing peanut seeds at three reproduction stages (R5, R6 and R7) from a resistant and a susceptible cultivated peanut genotypes, 'Tifrunner' (susceptible to <it>Aspergillus </it>infection with higher aflatoxin contamination and resistant to TSWV) and 'GT-C20' (resistant to <it>Aspergillus </it>with reduced aflatoxin contamination and susceptible to TSWV). The developing peanut seed tissues were challenged by <it>A. parasiticus </it>and drought stress in the field. A total of 24,192 randomly selected cDNA clones from six libraries were sequenced. After removing vector sequences and quality trimming, 21,777 high-quality EST sequences were generated. Sequence clustering and assembling resulted in 8,689 unique EST sequences with 1,741 tentative consensus EST sequences (TCs) and 6,948 singleton ESTs. Functional classification was performed according to MIPS functional catalogue criteria. The unique EST sequences were divided into twenty-two categories. A similarity search against the non-redundant protein database available from NCBI indicated that 84.78% of total ESTs showed significant similarity to known proteins, of which 165 genes had been previously reported in peanuts. There were differences in overall expression patterns in different libraries and genotypes. A number of sequences were expressed throughout all of the libraries, representing constitutive expressed sequences. In order to identify resistance-related genes with significantly differential expression, a statistical analysis to estimate the relative abundance (<it>R</it>) was used to compare the relative abundance of each gene transcripts in each cDNA library. Thirty six and forty seven unique EST sequences with threshold of <it>R </it>> 4 from libraries of 'GT-C20' and 'Tifrunner', respectively, were selected for examination of temporal gene expression patterns according to EST frequencies. Nine and eight resistance-related genes with significant up-regulation were obtained in 'GT-C20' and 'Tifrunner' libraries, respectively. Among them, three genes were common in both genotypes. Furthermore, a comparison of our EST sequences with other plant sequences in the TIGR Gene Indices libraries showed that the percentage of peanut EST matched to <it>Arabidopsis thaliana</it>, maize (<it>Zea mays</it>), <it>Medicago truncatula</it>, rapeseed (<it>Brassica napus</it>), rice (<it>Oryza sativa</it>), soybean (<it>Glycine max</it>) and wheat (<it>Triticum aestivum</it>) ESTs ranged from 33.84% to 79.46% with the sequence identity ≥ 80%. These results revealed that peanut ESTs are more closely related to legume species than to cereal crops, and more homologous to dicot than to monocot plant species.</p> <p>Conclusion</p> <p>The developed ESTs can be used to discover novel sequences or genes, to identify resistance-related genes and to detect the differences among alleles or markers between these resistant and susceptible peanut genotypes. Additionally, this large collection of cultivated peanut EST sequences will make it possible to construct microarrays for gene expression studies and for further characterization of host resistance mechanisms. It will be a valuable genomic resource for the peanut community. The 21,777 ESTs have been deposited to the NCBI GenBank database with accession numbers <ext-link ext-link-type="gen" ext-link-id="ES702769">ES702769</ext-link> to <ext-link ext-link-type="gen" ext-link-id="ES724546">ES724546</ext-link>.</p