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ABSTRACTDespite the advances in surface-display systems for directed evolution, variants with high affinity are not always enriched due to undesirable biases that increase target-unrelated variants during biopanning. Here, our goal was to design a library containing improved variants from the information of the “weakly enriched” library where functional variants were weakly enriched. Deep sequencing for the previous biopanning result, where no functional antibody mimetics were experimentally identified, revealed that weak enrichment was partly due to undesirable biases during phage infection and amplification steps. The clustering analysis of the deep sequencing data from appropriate steps revealed no distinct sequence patterns, but a Bayesian machine learning model trained with the selected deep sequencing data supplied nine clusters with distinct sequence patterns. Phage libraries were designed on the basis of the sequence patterns identified, and four improved variants with target-specific affinity (EC50 = 80–277 nM) were identified by biopanning. The selection and use of deep sequencing data without undesirable bias enabled us to extract the information on prospective variants. In summary, the use of appropriate deep sequencing data and machine learning with the sequence data has the possibility of finding sequence space where functional variants are enriched.

A majority of land plants can form symbiosis with arbuscular mycorrhizal (AM) fungi. MicroRNAs (miRNAs) have been implicated to regulate this process in legumes, but their involvement in non-legume species is largely unknown. In this study, by performing deep sequencing of sRNA libraries in tomato roots and comparing with tomato genome, a total of 700 potential miRNAs were predicted, among them, 187 are known plant miRNAs that have been previously deposited in miRBase. Unlike the profiles in other plants such as rice and Arabidopsis, a large proportion of predicted tomato miRNAs was 24 nt in length. A similar pattern was observed in the potato genome but not in tobacco, indicating a Solanum genus-specific expansion of 24-nt miRNAs. About 40% identified tomato miRNAs showed significantly altered expressions upon Rhizophagus irregularis inoculation, suggesting the potential roles of these novel miRNAs in AM symbiosis. The differential expression of five known and six novel miRNAs were further validated using qPCR analysis. Interestingly, three up-regulated known tomato miRNAs belong to a known miR171 family, a member of which has been reported in Medicago truncatula to regulate AM symbiosis. Thus, the miR171 family likely regulates AM symbiosis conservatively across different plant lineages. More than 1000 genes targeted by potential AM-responsive miRNAs were provided and their roles in AM symbiosis are worth further exploring.

Despite the advances in surface-display systems for directed evolution, variants with high affinity are not always enriched due to undesirable biases that increase target-unrelated variants during biopanning. Here, our goal was to design a library containing improved variants from the information of the "weakly enriched" library where functional variants were weakly enriched. Deep sequencing for the previous biopanning result, where no functional antibody mimetics were experimentally identified, revealed that weak enrichment was partly due to undesirable biases during phage infection and amplification steps. The clustering analysis of the deep sequencing data from appropriate steps revealed no distinct sequence patterns, but a Bayesian machine learning model trained with the selected deep sequencing data supplied nine clusters with distinct sequence patterns. Phage libraries were designed on the basis of the sequence patterns identified, and four improved variants with target-specific affinity (EC 50  = 80-277 nM) were identified by biopanning. The selection and use of deep sequencing data without undesirable bias enabled us to extract the information on prospective variants. In summary, the use of appropriate deep sequencing data and machine learning with the sequence data has the possibility of finding sequence space where functional variants are enriched.

Background: In a deep sequencing analysis of small RNAs prepared from a living fossil, the tadpole shrimp Triops cancriformis, a 32-nt small RNA was specifically detected in the adult stage. A nucleotide sequence comparison between the 32-nt small RNA and predicted tRNA sequences in the draft nuclear genomic DNA showed that the small RNA was derived from tRNAGly(GCC). To determine the overall features of the tRNA-derived fragments (tRFs) of T. cancriformis, the small RNA sequences in each of the six developmental stages (egg, 1st - 4th instar larvae, and adult) were compared with the mitochondrial and nuclear tRNA sequences. Results: We found that the tRFs were derived from mitochondrial and nuclear tRNAs corresponding to 16 and 39 anticodons, respectively. The total read number of nuclear tRFs was approximately 400 times larger than the number of mitochondrial tRFs. Interestingly, the main regions in each parental tRNA from which these tRFs were derived differed, depending on the parental anticodon. Mitochondrial tRFSer(GCU)s were abundantly produced from the 5' half regions of the parental tRNA, whereas mitochondrial tRFVal(UAC)s were mainly produced from the 3' end regions. Highly abundant nuclear tRFs, tRFGly(GCC)s, tRFGly(CCC)s, tRFGlu(CUC)s, and tRFLys(CUU)s were derived from the 5' half regions of the parental tRNAs. Further analysis of the tRF read counts in the individual developmental stages suggested that the expression of mitochondrial and nuclear tRFs differed during the six stages. Based on these data, we precisely summarized the positions of the tRFs in their parental tRNAs and their expression changes during development. Conclusions: Our results reveal the entire dynamics of the tRFs from both the nuclear and mitochondrial genomes of T. cancriformis and indicate that the majority of tRFs in the cell are derived from nuclear tRNAs. This study provides the first examples of developmentally expressed mitochondrial tRFs. [ABSTRACT FROM AUTHOR]

Background: MicroRNAs (miRNAs) are small non-coding RNAs that can exert multilevel inhibition/repression at a post-transcriptional or protein synthesis level during disease or development. Characterisation of miRNAs in adult mammalian brains by deep sequencing has been reported previously. However, to date, no small RNA profiling of the developing brain has been undertaken using this method. We have performed deep sequencing and small RNA analysis of a developing (E15.5) mouse brain. Results: We identified the expression of 294 known miRNAs in the E15.5 developing mouse brain, which were mostly represented by let-7 family and other brain-specific miRNAs such as miR-9 and miR-124. We also discovered 4 putative 22-23 nt miRNAs: mm_br_e15_1181, mm_br_e15_279920, mm_br_e15_96719 and mm_br_e15_294354 each with a 70-76 nt predicted pre-miRNA. We validated the 4 putative miRNAs and further characterised one of them, mm_br_e15_1181, throughout embryogenesis. Mm_br_e15_1181 biogenesis was Dicer1-dependent and was expressed in E3.5 blastocysts and E7 whole embryos. Embryo-wide expression patterns were observed at E9.5 and E11.5 followed by a near complete loss of expression by E13.5, with expression restricted to a specialised layer of cells within the developing and early postnatal brain. Mm_br_e15_1181 was upregulated during neurodifferentiation of P19 teratocarcinoma cells. This novel miRNA has been identified as miR-3099. Conclusions: We have generated and analysed the first deep sequencing dataset of small RNA sequences of the developing mouse brain. The analysis revealed a novel miRNA, miR-3099, with potential regulatory effects on early embryogenesis, and involvement in neuronal cell differentiation/function in the brain during late embryonic and early neonatal development. [ABSTRACT FROM AUTHOR]

Abstract: Double stranded RNA, isolated from 44 pooled randomly selected vines from a diseased South African vineyard, has been used in a deep sequencing analysis to build a census of the viral population. The dsRNA was sequenced in an unbiased manner using the sequencing-by-synthesis technology offered by the Illumina Genome Analyzer II and yielded 837 megabases of metagenomic sequence data. Four known viral pathogens were identified. It was found that Grapevine leafroll-associated virus 3 (GLRaV-3) is the most prevalent species, constituting 59% of the total reads, followed by Grapevine rupestris stem pitting-associated virus and Grapevine virus A. Grapevine virus E, a virus not previously reported in South African vineyards, was identified in the census. Viruses not previously identified in grapevine were also detected. The second most prevalent virus detected was a member of the Chrysoviridae family similar to Penicillium chrysogenum virus. Sequences aligning to two other mycoviruses were also detected. [Copyright &y& Elsevier]

We investigated the responses of microRNAs (miRNAs) using mouse embryonic stem cells (mESCs) exposed to nine chemicals (bis(2-ethylhexyl)phthalate, p -cresol, p -dichlorobenzene, phenol, pyrocatecol, chloroform, tri- n -butyl phosphate, trichloroethylene, and benzene), which are listed as "Class I Designated Chemical Substances" from the Japan Pollutant Release and Transfer Register. Using deep sequencing analysis (RNA-seq), several miRNAs were identified that show a substantial response to general chemical toxicity (i.e., to these nine chemicals considered as a group) and several miRNA biomarkers that show a substantial and specific response to benzene. The functions of the identified miRNAs were investigated in accordance with Gene Ontology terms of their predicted target genes, indicating regulation of cellular processes. We compared the results with those for the long non-coding RNAs (ncRNAs) and mRNAs reported in our previous studies in addition to previously identified miRNAs that are either up- or down-regulated in response to the benzene as stimuli. We also observed that the changes in expression of miRNAs were smaller than those for long ncRNAs and mRNAs. Taken together the current and previous results revealed that toxic chemical stimuli regulate the expression of miRNAs. We believe that the use of miRNAs, including the thus identified miRNAs, as biomarkers contribute to predicting the potential toxicity of particular chemicals or identifying human individuals that have been exposed to chemical hazards. • Investigation of miRNAs expression using mESCs exposed to nine chemicals by RNA-seq. • Identification of novel miRNA biomarkers responsive to general chemical toxicity. • GO analysis reveals the miRNAs affect genes for regulation of cellular processes. • The miRNAs are potentials indicators for chemical stimuli like other reported RNAs. [ABSTRACT FROM AUTHOR]

Maize can form symbiotic relationships with arbuscular mycorrhiza (AM) fungus to increase productivity and resistance, but the miRNAs in maize responsible for this process have not been discovered. In this study, 155 known and 28 novel miRNAs were identified by performing high-throughput sequencing of sRNA in maize roots colonized by AM fungi. Similar to the profiles in other AM-capable plants, a large proportion of identified maize miRNAs were 24 nt in length. Fourteen and two miRNAs were significantly down- and up-regulated in response to AM fungus Glomus intraradices inoculation, respectively, suggesting potential roles of these miRNAs in AM symbiosis. Interestingly, 12 of 14 significantly down-regulated known maize miRNAs belong to the miR399 family, which was previously reported to be involved in the interaction between Medicago truncatula and AM fungi. This result indicated that the miR399 family should regulate AM symbiosis conservatively across different plant lineages. Pathway and network analyses showed that the differentially expressed miRNAs might regulate lipid metabolism and phosphate starvation response in maize during the symbiosis process via their target genes. Several members of the miR399 family and the miR397 family should be involved in controlling the fatty acid metabolism and promoting lipid delivering from plants to AM fungi. To the best of our knowledge, this is the first report on miRNAs mediating fatty acids from plant to AM fungi. This study provides insight into the regulatory roles of miRNAs in the symbiosis between plants and AM fungi. [ABSTRACT FROM AUTHOR]

A majority of land plants can form symbiosis with arbuscular mycorrhizal (AM) fungi. MicroRNAs (miRNAs) have been implicated to regulate this process in legumes, but their involvement in non-legume species is largely unknown. In this study, by performing deep sequencing of sRNA libraries in tomato roots and comparing with tomato genome, a total of 700 potential miRNAs were predicted, among them, 187 are known plant miRNAs that have been previously deposited in miRBase. Unlike the profiles in other plants such as rice and Arabidopsis, a large proportion of predicted tomato miRNAs was 24 nt in length. A similar pattern was observed in the potato genome but not in tobacco, indicating a Solanum genus-specific expansion of 24-nt miRNAs. About 40% identified tomato miRNAs showed significantly altered expressions upon Rhizophagus irregularis inoculation, suggesting the potential roles of these novel miRNAs in AM symbiosis. The differential expression of five known and six novel miRNAs were further validated using qPCR analysis. Interestingly, three up-regulated known tomato miRNAs belong to a known miR171 family, a member of which has been reported in Medicago truncatula to regulate AM symbiosis. Thus, the miR171 family likely regulates AM symbiosis conservatively across different plant lineages. More than 1000 genes targeted by potential AM-responsive miRNAs were provided and their roles in AM symbiosis are worth further exploring.