Development of Computational Tools and Resources for Cotton microRNA Analysis

MicroRNAs (miRNAs) are an extensive class of small regulatory RNAs which regulate gene expression at the posttranscriptional levels. miRNAs target genes for mRNA cleavage or translation inhibition based on the complementary between the mRNAs and its corresponding miRNAs, and these miRNA target genes control development timing, organ development and response to environmental stress; thus miRNAs have been shown to play important roles in almost all biological and metabolic processes. Upland cotton (Gossypium hirsutum L.), one of the most important fiber producing crops, is widely planted in the world. Upland cotton originated from the reunion of two ancestral cotton genomes (A and D genomes) approximately 1-2 Myr ago, owning a complicated genome of allotetraploid (AADD, 2n=4x=52), with a haploid genome size estimated to be around 2.5 Gb. To date, about 80 miRNAs have been subsequentially identified in cotton by computational prediction or small RNA sequencing, many of which were also shown to be expressed differentially during fiber development. However, although miRNA-related research has become one of the hottest research in biology in the past decade and thousands of miRNAs have been identified, miRNA-related research in cotton is far beyond other plant species. One of the major reason is because of limited computational tools and resources for cotton. In this dissertation project, we first developed a comprehensive computational tool named miRDeepFinder, which can be used for miRNA identification, target prediction and GO-/KEGG-based functional analysis for both model and non-model plant species. A case study with a small RNA sequencing data of Arabidopsis showed miRDeepFinder is an accurate and robust tool for plant miRNA analysis in deep sequencing, since 12 of 13 novel miRNAs in Arabidopsis identified by miRDeepFinder were further confirmed by qRT-PCR. miRDeepFinder also incorporated the popularly-used Cleaveland software package for analysis of degradome sequencing data. Although cotton genome is still not available, huge cotton ESTs could be a good data resource for identification of cotton miRNAs and their targets. To better utilize cotton ESTs for miRNA identification, we globally re-assembled all the cotton ESTs and developed it to a cotton EST database, in which cotton coding genes and miRNAs were deeply annotated using BLASTx, BLASTn, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) resources. A total of 28,432 unique contigs were assembled from all 268,786 cotton ESTs currently available, belonging into 5,461 groups with a maximum cluster size of 196 members. Using these contigs, we also performed EST-based investigations of comparative transcriptome similarity between cotton and other plant species, sequence polymorphisms, expressed miRNAs and their targets, and SSR analysis. A total of 27,956 indel mutants and 149,616 single nucleotide polymorphisms (SNPs) were identified from consensus contigs. In a comparison with six model plant species, cotton ESTs show the highest overall similarity to grape. We also identified 151 and 4,214 EST-simple sequence repeats (SSRs) from contigs and raw ESTs respectively. Finally, all results were integrated to a comprehensive web-based cotton EST database (www.leonxie.com), in order to make these data widely available, and to facilitate access to EST-related genetic information. Subsequently, 3 cotton small RNA sequencing libraries treated by control, drought and salinity were sequenced. Based on miRDeepFinder, annotated cotton EST database, and cotton D genome of Gossypium raimondii, we identified 337 miRNAs with precursors in total, including 289 known miRNAs and 48 novel miRNAs. 155 of 337 miRNAs were found to be expressed differentially amongst the three treatments. Target prediction, GO-based functional classification, and KEGG-based functional enrichment uncovered many miRNAs and their stress-related targets might play roles in response to salinity and drought stresses. Using CitationRank-based literature mining, we sorted out the importance of genes related to stress of drought and salinity, respectively. It turned out NAC family, MYB family and MAPK family were ranked top under the context of drought and salinity, indicating their important roles for plant to combat stress of drought and salinity. To identify potential miRNAs and mRNA genes that significantly contribute to cotton fiber development, we constructed two libraries of 1-DPA (days post anthesis)-old leaf and ovule and sequenced them. A total of 128 pre-miRNAs, including 120 conserved and 8 novel pre-miRNAs were identified in cotton by miRDeepFinder. At least 40 miRNAs were either leaf or ovule-specific, whereas 62 miRNAs were shared in both leaf and ovule. Many transcription factors and other genes important for development of fiber were predicted to be miRNA targets. 22 predicted miRNA-target pairs were further validated by degradome sequencing analysis. In addition to miRNAs, we also identified 11 potential tasiRNAs-derived genes, many of which also might be involved in fiber development. miRNAs from cotton A and D genomes that reunioned together ~1-2 Myr ago might experience similar evolution pattern with coding genes. However, little is known about miRNA origin, expansion, loss, duplication, whether different derived miRNAs exchange with or affect each other, and how different genome-derived miRNAs and different genome-derived coding gene interact in cotton. To this, we systematically investigated miRNA expansion, expression pattern, miRNA targets amongst three cotton species Gossypium hirsutum (AADD), Gossypium arboreum (AA), Gossypium raimondii (DD). The origin of miRNAs and coding genes were the first to be categorized in upland cotton. Our results also showed that cotton-specific miRNAs might undergo remarkably expansion and some highly conserved miRNAs were likely to be lost despite most of conserved miRNAs were remained after genome polyploidization. The comparison of miRNA expression during seedling and fiber at 5 developmental stages revealed that different genome-derived miRNAs and miRNA*s displayed asymmetric expression pattern, implicating their diverse function in upland cotton phenotype. Upon all the identified miRNAs identified in upland cotton above, we also globally investigated miRNA modification features in cotton. Besides the observation of some similar modification features with other plant species in cotton, we also found many interesting modification forms, such as modification balance between 5' and 3' end miRNAs. Comparison of isomiR expression shows differential miRNA modification amongst the 6 developmental stages in terms of selective modification form, development-dependent modification, and differential expression abundance. In contrast to previous reports, cytodine is more frequently truncated and tailed from the two ends of isomiRs in cotton, implying existence of a complex cytodine balance in isomiRs. Together, we developed a comprehensive computational tool and data resource for cotton miRNA research, and used these tools to investigate miRNA roles in cotton fiber development and response to abiotic stress. Cotton miRNA evolution and modification were also studied. Thus, our tools, data resources and research findings would contribute us to deciphering miRNA regulatory function and evolution in cotton.Ph.D

Deep sequencing reveals important roles of microRNAs in response to drought and salinity stress in cotton

Drought and salinity are two major environmental factors adversely affecting plant growth and productivity. However, the regulatory mechanism is unknown. In this study, the potential roles of small regulatory microRNAs (miRNAs) in cotton response to those stresses were investigated. Using next-generation deep sequencing, a total of 337 miRNAs with precursors were identified, comprising 289 known miRNAs and 48 novel miRNAs. Of these miRNAs, 155 miRNAs were expressed differentially. Target prediction, Gene Ontology (GO)-based functional classification, and Kyoto Encyclopedia of Genes and Genomes (KEGG)-based functional enrichment show that these miRNAs might play roles in response to salinity and drought stresses through targeting a series of stress-related genes. Degradome sequencing analysis showed that at least 55 predicted target genes were further validated to be regulated by 60 miRNAs. CitationRank-based literature mining was employed to determinhe the importance of genes related to drought and salinity stress. The NAC, MYB, and MAPK families were ranked top under the context of drought and salinity, indicating their important roles for the plant to combat drought and salinity stress. According to target prediction, a series of cotton miRNAs are associated with these top-ranked genes, including miR164, miR172, miR396, miR1520, miR6158, ghr-n24, ghr-n56, and ghr-n59. Interestingly, 163 cotton miRNAs were also identified to target 210 genes that are important in fibre development. These results will contribute to cotton stress-resistant breeding as well as understanding fibre development

Genome sequencing and analysis of the paclitaxelproducing endophytic fungus \u3cem\u3ePenicillium aurantiogriseum\u3c/em\u3e NRRL 62431

Background Paclitaxel (Taxol™) is an important anticancer drug with a unique mode of action. The biosynthesis of paclitaxel had been considered restricted to the Taxus species until it was discovered in Taxomyces andreanae, an endophytic fungus of T. brevifolia. Subsequently, paclitaxel was found in hazel (Corylus avellana L.) and in several other endophytic fungi. The distribution of paclitaxel in plants and endophytic fungi and the reported sequence homology of key genes in paclitaxel biosynthesis between plant and fungi species raises the question about whether the origin of this pathway in these two physically associated groups could have been facilitated by horizontal gene transfer. Results The ability of the endophytic fungus of hazel Penicillium aurantiogriseum NRRL 62431 to independently synthesize paclitaxel was established by liquid chromatography-mass spectrometry and proton nuclear magnetic resonance. The genome of Penicillium aurantiogriseum NRRL 62431 was sequenced and gene candidates that may be involved in paclitaxel biosynthesis were identified by comparison with the 13 known paclitaxel biosynthetic genes in Taxus. We found that paclitaxel biosynthetic gene candidates in P. aurantiogriseum NRRL 62431 have evolved independently and that horizontal gene transfer between this endophytic fungus and its plant host is unlikely. Conclusions Our findings shed new light on how paclitaxel-producing endophytic fungi synthesize paclitaxel, and will facilitate metabolic engineering for the industrial production of paclitaxel from fungi

Genome-Wide Functional Analysis of the Cotton Transcriptome by Creating an Integrated EST Database

A total of 28,432 unique contigs (25,371 in consensus contigs and 3,061 as singletons) were assembled from all 268,786 cotton ESTs currently available. Several in silico approaches [comparative genomics, Blast, Gene Ontology (GO) analysis, and pathway enrichment by Kyoto Encyclopedia of Genes and Genomes (KEGG)] were employed to investigate global functions of the cotton transcriptome. Cotton EST contigs were clustered into 5,461 groups with a maximum cluster size of 196 members. A total of 27,956 indel mutants and 149,616 single nucleotide polymorphisms (SNPs) were identified from consensus contigs. Interestingly, many contigs with significantly high frequencies of indels or SNPs encode transcription factors and protein kinases. In a comparison with six model plant species, cotton ESTs show the highest overall similarity to grape. A total of 87 cotton miRNAs were identified; 59 of these have not been reported previously from experimental or bioinformatics investigations. We also predicted 3,260 genes as miRNAs targets, which are associated with multiple biological functions, including stress response, metabolism, hormone signal transduction and fiber development. We identified 151 and 4,214 EST-simple sequence repeats (SSRs) from contigs and raw ESTs respectively. To make these data widely available, and to facilitate access to EST-related genetic information, we integrated our results into a comprehensive, fully downloadable web-based cotton EST database (www.leonxie.com)

Identification, characterization, and gene expression analysis of nucleotide binding site (NB)-type resistance gene homologues in switchgrass

Abstract Background Switchgrass (Panicum virgatum L.) is a warm-season perennial grass that can be used as a second generation bioenergy crop. However, foliar fungal pathogens, like switchgrass rust, have the potential to significantly reduce switchgrass biomass yield. Despite its importance as a prominent bioenergy crop, a genome-wide comprehensive analysis of NB-LRR disease resistance genes has yet to be performed in switchgrass. Results In this study, we used a homology-based computational approach to identify 1011 potential NB-LRR resistance gene homologs (RGHs) in the switchgrass genome (v 1.1). In addition, we identified 40 RGHs that potentially contain unique domains including major sperm protein domain, jacalin-like binding domain, calmodulin-like binding, and thioredoxin. RNA-sequencing analysis of leaf tissue from ‘Alamo’, a rust-resistant switchgrass cultivar, and ‘Dacotah’, a rust-susceptible switchgrass cultivar, identified 2634 high quality variants in the RGHs between the two cultivars. RNA-sequencing data from field-grown cultivar ‘Summer’ plants indicated that the expression of some of these RGHs was developmentally regulated. Conclusions Our results provide useful insight into the molecular structure, distribution, and expression patterns of members of the NB-LRR gene family in switchgrass. These results also provide a foundation for future work aimed at elucidating the molecular mechanisms underlying disease resistance in this important bioenergy crop

Genome of Wild Olive and the Evolution of Oil Biosynthesis

Here we present the genome sequence and annotation of the wild olive tree (Olea europaea var. sylvestris), called oleaster, which is considered an ancestor of cultivated olive trees. More than 50,000 protein-coding genes were predicted, a majority of which could be anchored to 23 pseudochromosomes obtained through a newly constructed genetic map. The oleaster genome contains signatures of two Oleaceae lineage-specific paleopolyploidy events, dated at similar to 28 and similar to 59 Mya. These events contributed to the expansion and neo-functionalization of genes and gene families that play important roles in oil biosynthesis. The functional divergence of oil biosynthesis pathway genes, such as FAD2, SACPD, EAR, and ACPTE, following duplication, has been responsible for the differential accumulation of oleic and linoleic acids produced in olive compared with sesame, a closely related oil crop. Duplicated oleaster FAD2 genes are regulated by an siRNA derived from a transposable element-rich region, leading to suppressed levels of FAD2 gene expression. Additionally, neofunctionalization of members of the SACPD gene family has led to increased expression of SACPD2,3, 5, and 7, consequently resulting in an increased desaturation of steric acid. Taken together, decreased FAD2 expression and increased SACPD expression likely explain the accumulation of exceptionally high levels of oleic acid in olive. The oleaster genome thus provides important insights into the evolution of oil biosynthesis and will be a valuable resource for oil crop genomics

Development of Computational Tools and Resources for Cotton microRNA Analysis

MicroRNAs (miRNAs) are an extensive class of small regulatory RNAs which regulate gene expression at the posttranscriptional levels. miRNAs target genes for mRNA cleavage or translation inhibition based on the complementary between the mRNAs and its corresponding miRNAs, and these miRNA target genes control development timing, organ development and response to environmental stress\; thus miRNAs have been shown to play important roles in almost all biological and metabolic processes. Upland cotton (Gossypium hirsutum L.), one of the most important fiber producing crops, is widely planted in the world. Upland cotton originated from the reunion of two ancestral cotton genomes (A and D genomes) approximately 1-2 Myr ago, owning a complicated genome of allotetraploid (AADD, 2n=4x=52), with a haploid genome size estimated to be around 2.5 Gb. To date, about 80 miRNAs have been subsequentially identified in cotton by computational prediction or small RNA sequencing, many of which were also shown to be expressed differentially during fiber development. However, although miRNA-related research has become one of the hottest research in biology in the past decade and thousands of miRNAs have been identified, miRNA-related research in cotton is far beyond other plant species. One of the major reason is because of limited computational tools and resources for cotton. In this dissertation project, we first developed a comprehensive computational tool named miRDeepFinder, which can be used for miRNA identification, target prediction and GO-/KEGG-based functional analysis for both model and non-model plant species. A case study with a small RNA sequencing data of Arabidopsis showed miRDeepFinder is an accurate and robust tool for plant miRNA analysis in deep sequencing, since 12 of 13 novel miRNAs in Arabidopsis identified by miRDeepFinder were further confirmed by qRT-PCR. miRDeepFinder also incorporated the popularly-used Cleaveland software package for analysis of degradome sequencing data. Although cotton genome is still not available, huge cotton ESTs could be a good data resource for identification of cotton miRNAs and their targets. To better utilize cotton ESTs for miRNA identification, we globally re-assembled all the cotton ESTs and developed it to a cotton EST database, in which cotton coding genes and miRNAs were deeply annotated using BLASTx, BLASTn, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) resources. A total of 28,432 unique contigs were assembled from all 268,786 cotton ESTs currently available, belonging into 5,461 groups with a maximum cluster size of 196 members. Using these contigs, we also performed EST-based investigations of comparative transcriptome similarity between cotton and other plant species, sequence polymorphisms, expressed miRNAs and their targets, and SSR analysis. A total of 27,956 indel mutants and 149,616 single nucleotide polymorphisms (SNPs) were identified from consensus contigs. In a comparison with six model plant species, cotton ESTs show the highest overall similarity to grape. We also identified 151 and 4,214 EST-simple sequence repeats (SSRs) from contigs and raw ESTs respectively. Finally, all results were integrated to a comprehensive web-based cotton EST database (www.leonxie.com), in order to make these data widely available, and to facilitate access to EST-related genetic information. Subsequently, 3 cotton small RNA sequencing libraries treated by control, drought and salinity were sequenced. Based on miRDeepFinder, annotated cotton EST database, and cotton D genome of Gossypium raimondii, we identified 337 miRNAs with precursors in total, including 289 known miRNAs and 48 novel miRNAs. 155 of 337 miRNAs were found to be expressed differentially amongst the three treatments. Target prediction, GO-based functional classification, and KEGG-based functional enrichment uncovered many miRNAs and their stress-related targets might play roles in response to salinity and drought stresses. Using CitationRank-based literature mining, we sorted out the importance of genes related to stress of drought and salinity, respectively. It turned out NAC family, MYB family and MAPK family were ranked top under the context of drought and salinity, indicating their important roles for plant to combat stress of drought and salinity. To identify potential miRNAs and mRNA genes that significantly contribute to cotton fiber development, we constructed two libraries of 1-DPA (days post anthesis)-old leaf and ovule and sequenced them. A total of 128 pre-miRNAs, including 120 conserved and 8 novel pre-miRNAs were identified in cotton by miRDeepFinder. At least 40 miRNAs were either leaf or ovule-specific, whereas 62 miRNAs were shared in both leaf and ovule. Many transcription factors and other genes important for development of fiber were predicted to be miRNA targets. 22 predicted miRNA-target pairs were further validated by degradome sequencing analysis. In addition to miRNAs, we also identified 11 potential tasiRNAs-derived genes, many of which also might be involved in fiber development. miRNAs from cotton A and D genomes that reunioned together ~1-2 Myr ago might experience similar evolution pattern with coding genes. However, little is known about miRNA origin, expansion, loss, duplication, whether different derived miRNAs exchange with or affect each other, and how different genome-derived miRNAs and different genome-derived coding gene interact in cotton. To this, we systematically investigated miRNA expansion, expression pattern, miRNA targets amongst three cotton species Gossypium hirsutum (AADD), Gossypium arboreum (AA), Gossypium raimondii (DD). The origin of miRNAs and coding genes were the first to be categorized in upland cotton. Our results also showed that cotton-specific miRNAs might undergo remarkably expansion and some highly conserved miRNAs were likely to be lost despite most of conserved miRNAs were remained after genome polyploidization. The comparison of miRNA expression during seedling and fiber at 5 developmental stages revealed that different genome-derived miRNAs and miRNA*s displayed asymmetric expression pattern, implicating their diverse function in upland cotton phenotype. Upon all the identified miRNAs identified in upland cotton above, we also globally investigated miRNA modification features in cotton. Besides the observation of some similar modification features with other plant species in cotton, we also found many interesting modification forms, such as modification balance between 5' and 3' end miRNAs. Comparison of isomiR expression shows differential miRNA modification amongst the 6 developmental stages in terms of selective modification form, development-dependent modification, and differential expression abundance. In contrast to previous reports, cytodine is more frequently truncated and tailed from the two ends of isomiRs in cotton, implying existence of a complex cytodine balance in isomiRs. Together, we developed a comprehensive computational tool and data resource for cotton miRNA research, and used these tools to investigate miRNA roles in cotton fiber development and response to abiotic stress. Cotton miRNA evolution and modification were also studied. Thus, our tools, data resources and research findings would contribute us to deciphering miRNA regulatory function and evolution in cotton

Transcriptional Profiling Reveals Key Regulatory Roles of the WUSCHEL-Related Homeobox Gene Family in Yellowhorn (<i>Xanthoceras sorbifolia</i> Bunge)

The WUSCHEL-related homeobox (WOX) gene family plays a crucial role in regulating embryonic development, organ formation, and stress resistance. Yellowhorn (Xanthoceras sorbifolia Bunge), a drought-resistant tree known for its oil production, lacks sufficient information regarding the WOX gene family. To understand the evolutionary mechanisms and potential functions of this gene family in yellowhorn, we conducted a comprehensive investigation on its expression patterns and evolutionary characteristics. Our analysis revealed the presence of nine XsWOX genes in the yellowhorn genome, which could be categorized into three distinct clades through a phylogenetic analysis. A chromosomal localization analysis indicated that these nine XsWOX genes were situated on six out of the fifteen chromosomes. An intra-species collinear analysis revealed only one pair of tandem duplicated genes within the XsWOX family. The promoter regions of the XsWOX family were found to contain responsive cis-acting elements associated with plant growth and development, stress responses, and hormone signaling. Moreover, an analysis of the gene expression profiles in different developmental stages of callus revealed significant expressions of XsWOX1, XsWOX4, and XsWOX5 in embryogenic callus and somatic embryo formation, suggesting that they have special roles in regulating yellowhorn’s somatic embryogenesis. Furthermore, the expression level of XsWOX5 indicated its potential involvement not only in organ formation but also in responding to low temperature, salt, and saline-alkali stresses. Overall, our findings lay a solid foundation for future in-depth studies on the functionality and evolution of XsWOX genes in yellowhorn

Effects of Rainfall Intensity and Slope Gradient on Runoff and Soil Moisture Content on Different Growing Stages of Spring Maize

The rainfall-runoff process (RRP) is an important part of hydrologic process. There is an effective measure to study RRP through artificial rainfall simulation. This paper describes a study on three growing stages (jointing stage, tasseling stage, and mature stage) of spring maize in which simulated rainfall events were used to study the effects of various factors (rainfall intensity and slope gradient) on the RRP. The RRP was tested with three different rainfall intensities (0.67, 1.00, and 1.67 mm/min) and subjected to three different slopes (5°, 15°, and 20°) so as to study RRP characteristics in semiarid regions. Regression analysis was used to study the results of this test. The following key results were obtained: (1) With the increase in rainfall intensity and slope, the increasing relationship with rainfall duration, overland flow, and cumulative runoff, respectively, complied with logarithmic and quadratic functions before reaching stable runoff in each growing stage of spring maize; (2) The runoff coefficient increased with the increase in rainfall intensity and slope in each growing stages of spring maize. The relationship between runoff coefficient, slope, rainfall intensity, rainfall duration, antecedent soil moisture, and vegetation coverage was multivariate and nonlinear; (3) The runoff lag time decreased with the increase in rainfall intensity and slope within the same growing stage. In addition, the relationship between runoff lag time, slope, rainfall intensity, antecedent soil moisture, and vegetation coverage could also be expressed by a multivariate nonlinear equation; (4) The descent rate of soil infiltration rate curve increased with the increased rainfall intensity and slope in the same growing stage. Furthermore, by comparing the Kostiakov, Horton, and Philip models, it was found that the Horton infiltration model was the best for estimating soil infiltration rate and cumulative infiltration under the condition of test