Project description:Intensive application of inorganic nitrogen underlies marked increase in crop production yet imposes detrimental impact on ecosystems, hence it is crucial for future sustainable agriculture to improve nitrogen-use efficiency (NUE). Here we report the genetic basis of NUE associated with the local soil adaptation in rice. With a diverse rice germplasm panel collected from different ecogeographic regions, we performed genome-wide association study on tillering response to nitrogen (TRN), the most correlated trait with NUE of rice, and identified OsTCP19 as a modulator of TRN via transcriptionally responding to nitrogen and targeting to Dwarf and Low-Tillering (DLT), a tiller-promoting gene. A 29-bp InDel in OsTCP19 promoter confers differential transcription response to nitrogen and TRN variation among rice varieties. The high-TRN allele of OsTCP19 (OsTCP19-H) is prevalent in wild rice population, but largely lost in modern cultivars correlating with increased local soil nitrogen content, suggesting that it might have contributed to geographic adaptation in rice. Introgression of OsTCP19-H into modern rice cultivars boosts grain yield and NUE under low or moderate nitrogen levels, demonstrating its enormous potential for rice breeding and environment amelioration through reducing nitrogen application.
Project description:Purpose: Deconstructing the soil microbiome into reduced-complexity functional modules represents a novel method of microbiome analysis. The goals of this study are to confirm differences in transcriptomic patterns among five functional module consortia. Methods: mRNA profiles of 3 replicates each of functional module enrichments of soil inoculum in M9 media with either 1) xylose, 2) n-acetylglucosamine, 3) glucose and gentamycin, 4) xylan, or 5) pectin were generated by sequencing using an Illumina platform (GENEWIZ performed sequencing). Sequence reads that passed quality filters were aligned to a soil metagenome using Burrows Wheeler Aligner. Resulting SAM files were converted to raw reads using HTSeq, and annotated using Uniref90 or EGGNOG databases. Results: To reduce the size of the RNA-Seq counts table and increase its computational tractability, transcripts containing a minimum of 75 total counts, but no more than 3 zero counts, across the 15 samples were removed. The subsequent dataset was normalized using DESeq2, resulting in a dataset consisting of 6947 unique transcripts across the 15 samples, and 185,920,068 reads. We identified gene categories that were enriched in a sample type relative to the overall dataset using Fisher’s exact test. Conclusions: our dataset confirms that the functional module consortia generated from targeted enrichments of a starting soil inoculum had distinct functional trends by enrichment type.
Project description:We aimed to identify putative ABA-regulated miRNAs expressed in rice by using a deep sequencing approach developed by Solexa (Illumina). Two small RNA libraries were constructed from Osaba1-1 and wild type rice leaves, and more than ten million small RNA sequence reads were generated for each library. We identified 13 ABA-regulated miRNAs via expression profiling of the miRNAs based on a comparative miRNAomic analysis in combination with experimental validation. To the best of our knowledge, this is the first report of a systematic investigation of ABA-regulated miRNAs and their targets in rice.