The early maize (Zea mays) seed undergoes several developmental stages after double fertilization to become fully differentiated within a short period of time, but the genetic control of this highly dynamic and complex developmental process remains largely unknown. Here, we report a high temporal-resolution investigation of transcriptomes using 31 samples collected at an interval of 4 or 6 h within the first six days of seed development. These time-course transcriptomes were clearly separated into four distinct groups corresponding to the stages of double fertilization, coenocyte formation, cellularization, and differentiation. A total of 22,790 expressed genes including 1415 transcription factors (TFs) were detected in early stages of maize seed development. In particular, 1093 genes including 110 TFs were specifically expressed in the seed and displayed high temporal specificity by expressing only in particular period of early seed development. There were 160, 22, 112, and 569 seed-specific genes predominantly expressed in the first 16 h after pollination, coenocyte formation, cellularization, and differentiation stage, respectively. In addition, network analysis predicted 31,256 interactions among 1317 TFs and 14,540 genes. The high temporal-resolution transcriptome atlas reported here provides an important resource for future functional study to unravel the genetic control of seed development.

Background: MicroRNAs (miRNAs) are a class of short non-coding, endogenous RNAs that play key roles in many biological processes in both animals and plants. Although many miRNAs have been identified in a large number of organisms, the miRNAs in foxtail millet (Setaria italica) have, until now, been poorly understood. Results: In this study, two replicate small RNA libraries from foxtail millet shoots were sequenced, and 40 million reads representing over 10 million unique sequences were generated. We identified 43 known miRNAs, 172 novel miRNAs and 2 mirtron precursor candidates in foxtail millet. Some miRNA*s of the known and novel miRNAs were detected as well. Further, eight novel miRNAs were validated by stem-loop RT-PCR. Potential targets of the foxtail millet miRNAs were predicted based on our strict criteria. Of the predicted target genes, 79% (351) had functional annotations in InterPro and GO analyses, indicating the targets of the miRNAs were involved in a wide range of regulatory functions and some specific biological processes. A total of 69 pairs of syntenic miRNA precursors that were conserved between foxtail millet and sorghum were found. Additionally, stem-loop RT-PCR was conducted to confirm the tissue-specific expression of some miRNAs in the four tissues identified by deep-sequencing. Conclusions: We predicted, for the first time, 215 miRNAs and 447 miRNA targets in foxtail millet at a genome-wide level. The precursors, expression levels, miRNA* sequences, target functions, conservation, and evolution of miRNAs we identified were investigated. Some of the novel foxtail millet miRNAs and miRNA targets were validated experimentally.

Background: Low grain water content (GWC) at harvest of maize (Zea mays L.) is essential for mechanical harvesting, transportation and storage. Grain drying rate (GDR) is a key determinant of GWC. Many quantitative trait locus (QTLs) related to GDR and GWC have been reported, however, the confidence interval (CI) of these QTLs are too large and few QTLs has been fine-mapped or even been cloned. Meta-QTL (MQTL) analysis is an effective method to integrate QTLs information in independent populations, which helps to understand the genetic structure of quantitative traits. Results: In this study, MQTL analysis was performed using 282 QTLs from 25 experiments related GDR and GWC. Totally, 11 and 34 MQTLs were found to be associated with GDR and GWC, respectively. The average CI of GDR and GWC MQTLs was 24.44 and 22.13 cM which reduced the 57 and 65% compared to the average QTL interval for initial GDR and GWC QTL, respectively. Finally, 1494 and 5011 candidate genes related to GDR and GWC were identified in MQTL intervals, respectively. Among these genes, there are 48 genes related to hormone metabolism. Conclusions: Our studies combined traditional QTL analyses, genome-wide association study and RNA-seq to analysis major locus for regulating GWC in maize.

To properly understand cotton responses to potassium (K⁺) deficiency and how its shoot feedback regulates K⁺ uptake and root growth, we analyzed the changes in root transcriptome induced by low K⁺ (0.03 mM K⁺, lasting three days) in self-grafts of a K⁺ inefficient cotton variety (CCRI41/CCRI41, scion/rootstock) and its reciprocal grafts with a K⁺ efficient variety (SCRC22/CCRI41). Compared with CCRI41/CCRI41, the SCRC22 scion enhanced the K⁺ uptake and root growth of CCRI41 rootstock. A total of 1968 and 2539 differently expressed genes (DEGs) were identified in the roots of CCRI41/CCRI41 and SCRC22/CCRI41 in response to K⁺ deficiency, respectively. The overlapped and similarly (both up- or both down-) regulated DEGs in the two grafts were considered the basic response to K⁺ deficiency in cotton roots, whereas the DEGs only found in SCRC22/CCRI41 (1954) and those oppositely (one up- and the other down-) regulated in the two grafts might be the key factors involved in the feedback regulation of K⁺ uptake and root growth. The expression level of four putative K⁺ transporter genes (three GhHAK5s and one GhKUP3) increased in both grafts under low K⁺, which could enable plants to cope with K⁺ deficiency. In addition, two ethylene response factors (ERFs), GhERF15 and GhESE3, both down-regulated in the roots of CCRI41/CCRI41 and SCRC22/CCRI41, may negatively regulate K⁺ uptake in cotton roots due to higher net K⁺ uptake rate in their virus-induced gene silencing (VIGS) plants. In terms of feedback regulation of K⁺ uptake and root growth, several up-regulated DEGs related to Ca²⁺ binding and CIPK (CBL-interacting protein kinases), one up-regulated GhKUP3 and several up-regulated GhNRT2.1s probably play important roles. In conclusion, these results provide a deeper insight into the molecular mechanisms involved in basic response to low K⁺ stress in cotton roots and feedback regulation of K⁺ uptake, and present several low K⁺ tolerance-associated genes that need to be further identified and characterized.