Plants depend upon beneficial interactions between roots and microbes for nutrient availability, growth promotion, and disease suppression. High-throughput sequencing approaches have provided recent insights into root microbiomes, but our current understanding is still limited relative to animal microbiomes. Here we present a detailed characterization of the root-associated microbiomes of the crop plant rice by deep sequencing, using plants grown under controlled conditions as well as field cultivation at multiple sites. The spatial resolution of the study distinguished three root-associated compartments, the endosphere (root interior), rhizoplane (root surface), and rhizosphere (soil close to the root surface), each of which was found to harbor a distinct microbiome. Under controlled greenhouse conditions, microbiome composition varied with soil source and genotype. In field conditions, geographical location and cultivation practice, namely organic vs. conventional, were factors contributing to microbiome variation. Rice cultivation is a major source of global methane emissions, and methanogenic archaea could be detected in all spatial compartments of field-grown rice. The depth and scale of this study were used to build coabundance networks that revealed potential microbial consortia, some of which were involved in methane cycling. Dynamic changes observed during microbiome acquisition, as well as steady-state compositions of spatial compartments, support a multistep model for root microbiome assembly from soil wherein the rhizoplane plays a selective gating role. Similarities in the distribution of phyla in the root microbiomes of rice and other plants suggest that conclusions derived from this study might be generally applicable to land plants.

Mutants of a new gene, TRANSPARENT TESTA GLABRA2 ( TTG2 ), show disruptions to trichome development and to tannin and mucilage production in the seed coat. The gene was tagged by the endogenous transposon Tag1 and shown to encode a WRKY transcription factor. It is the first member of this large, plant-specific family known to control morphogenesis. The functions of all other WRKY genes revealed to date involve responses to pathogen attack, mechanical stress, and senescence. TTG2 is strongly expressed in trichomes throughout their development, in the endothelium of developing seeds (in which tannin is later generated) and subsequently in other layers of the seed coat, and in the atrichoblasts of developing roots. TTG2 acts downstream of the trichome initiation genes TTG1 and GLABROUS1 , although trichome expression of TTG2 continues to occur if they are inactivated. Later, TTG2 shares functions with GLABRA2 in controlling trichome outgrowth. In the seed coat, TTG2 expression requires TTG1 function in the production of tannin. Finally, TTG2 also may be involved in specifying atrichoblasts in roots redundantly with other gene(s) but independently of TTG1 and GLABRA2 .

The plant life cycle involves an alternation of generations between sporophyte and gametophyte. Currently, the genes and pathways involved in gametophytic development and function in flowering plants remain largely unknown. A large-scale mutant screen of Ds transposon insertion lines was employed to identify 130 mutants of Arabidopsis thaliana with defects in female gametophyte development and function. A wide variety of mutant phenotypes were observed, ranging from defects in different stages of early embryo sac development to mutants with apparently normal embryo sacs, but exhibiting defects in processes such as pollen tube guidance, fertilization or early embryo development. Unexpectedly, nearly half of the mutants isolated in this study were found to be primarily defective in post-fertilization processes dependent on the maternal allele, suggesting that genes expressed from the female gametophyte or the maternal genome play a major role in the early development of plant embryos. Sequence identification of the genes disrupted in the mutants revealed genes involved in protein degradation, cell death, signal transduction and transcriptional regulation required for embryo sac development, fertilization and early embryogenesis. These results provide a first comprehensive overview of the genes and gene products involved in female gametophyte development and function within a flowering plant.

To address the role of small regulatory RNAs in rice development, we generated a large data set of small RNAs from mature leaves and developing roots, shoots, and inflorescences. Using a spatial clustering algorithm, we identified 36,780 genomic groups of small RNAs. Most consisted of 24-nt RNAs that are expressed in all four tissues and enriched in repeat regions of the genome; 1029 clusters were composed primarily of 21-nt small RNAs and, strikingly, 831 of these contained phased RNAs and were preferentially expressed in developing inflorescences. Thirty-eight of the 24-mer clusters were also phased and preferentially expressed in inflorescences. The phased 21-mer clusters derive from nonprotein coding, nonrepeat regions of the genome and are grouped together into superclusters containing 10-46 clusters. The majority of these 21-mer clusters (705/831) are flanked by a degenerate 22-nt motif that is offset by 12 nt from the main phase of the cluster. Small RNAs complementary to these flanking 22-nt motifs define a new miRNA family, which is conserved in maize and expressed in developing reproductive tissues in both plants. These results suggest that the biogenesis of phased inflorescence RNAs resembles that of tasiRNAs and raise the possibility that these novel small RNAs function in early reproductive development in rice and other monocots.

MicroRNAs (miRNAs) are post-transcriptional regulators of gene expression in animals and plants. Comparative genomic computational methods have been developed to predict new miRNAs in worms, flies, and humans. Here, we present a novel single genome approach for the detection of miRNAs in Arabidopsis thaliana. This was initiated by producing a candidate miRNA-target data set using an algorithm called findMiRNA, which predicts potential miRNAs within candidate precursor sequences that have corresponding target sites within transcripts. From this data set, we used a characteristic divergence pattern of miRNA precursor families to select 13 potential new miRNAs for experimental verification, and found that corresponding small RNAs could be detected for at least eight of the candidate miRNAs. Expression of some of these miRNAs appears to be under developmental control. Our results are consistent with the idea that targets of miRNAs encompass a wide range of transcripts, including those for F-box factors, ubiquitin conjugases, Leucine-rich repeat proteins, and metabolic enzymes, and that regulation by miRNAs might be widespread in the genome. The entire set of annotated transcripts in the Arabidopsis genome has been run through findMiRNA to yield a data set that will enable identification of potential miRNAs directed against any target gene.