Project description:The debate on the origin and evolution of flowers has recently entered the field of developmental genetics, with focus on the design of the ancestral floral regulatory program. Flowers can differ dramatically among angiosperm lineages, but in general, sterile perianth organs surrounding stamens (male reproductive organs) and carpels (female reproductive organs) constitute the basic floral structure. However, the basal angiosperm lineages exhibit spectacular diversity in the number, arrangement, and structure, of floral organs, while the evolutionarily derived monocot and eudicot lineages share a far more uniform floral ground plan. As such, regulatory mechanisms underlying the archetypal floral plan, for instance that of the eudicot genetic model Arabidopsis thaliana, are unlikely to apply to the original flowers. Here we show that broadly overlapping transcriptional programs characterise the floral transcriptome of the basal angiosperm Persea americana (avocado), while floral gene expression domains are typically organ-specific in Arabidopsis. Our findings extend the “fading borders” model for basal angiosperms from organ identity genes to the downstream floral transcriptome, and suggest that the combinatorial mechanism for organ identity may not operate in basal angiosperms as it does in Arabidopsis. Furthermore, fading expression of components of the stamen transcriptome in central and peripheral regions of Persea flowers resembles the developmental program of the hypothesized gymnosperm “floral progenitor”. Accordingly, in contrast to the canalized organ-specific regulatory apparatus of Arabidopsis, floral development may have been originally regulated by overlapping transcriptional cascades with fading gradients of influence from focal to bordering organs.
Project description:The debate on the origin and evolution of flowers has recently entered the field of developmental genetics, with focus on the design of the ancestral floral regulatory program. Flowers can differ dramatically among angiosperm lineages, but in general, sterile perianth organs surrounding stamens (male reproductive organs) and carpels (female reproductive organs) constitute the basic floral structure. However, the basal angiosperm lineages exhibit spectacular diversity in the number, arrangement, and structure, of floral organs, while the evolutionarily derived monocot and eudicot lineages share a far more uniform floral ground plan. As such, regulatory mechanisms underlying the archetypal floral plan, for instance that of the eudicot genetic model Arabidopsis thaliana, are unlikely to apply to the original flowers. Here we show that broadly overlapping transcriptional programs characterise the floral transcriptome of the basal angiosperm Persea americana (avocado), while floral gene expression domains are typically organ-specific in Arabidopsis. Our findings extend the âfading bordersâ model for basal angiosperms from organ identity genes to the downstream floral transcriptome, and suggest that the combinatorial mechanism for organ identity may not operate in basal angiosperms as it does in Arabidopsis. Furthermore, fading expression of components of the stamen transcriptome in central and peripheral regions of Persea flowers resembles the developmental program of the hypothesized gymnosperm âfloral progenitorâ. Accordingly, in contrast to the canalized organ-specific regulatory apparatus of Arabidopsis, floral development may have been originally regulated by overlapping transcriptional cascades with fading gradients of influence from focal to bordering organs. Expression profiles of inflorescence buds, pre-meiotic floral buds, inner and outer tepals, stamens, carpels, initiating fruit, and leaves were assessed in an interwoven double loop design for eight samples with 16 arrays. Sample materials were collected from two individuals (biological replicates) cultivated on the University of Floridaâs Gainesville campus, and RNA was isolated twice for technical replication. Thus, four RNA extractions from each of the eight tissue types listed above were individually labeled with Cy3 (twice) or Cy5 (twice) and hybridized with four other Cy3 or Cy5 labeled samples as a dual channel array system.
Project description:Small RNAs (21-24 nt) are pivotal regulators of gene expression that guide both transcriptional and post-transcriptional silencing mechanisms in diverse eukaryotes, including most if not all plants. MicroRNAs (miRNAs) and short interfering RNAs (siRNAs) are the two major types, both of which have a demonstrated and important role in plant development, stress responses and pathogen resistance. In this work, we used a deep sequencing approach (Sequencing-By-Synthesis, or SBS) to develop sequence resources of small RNAs from Persea americana tissues (including leaves, flowers and fruit). The high depth of the resulting datasets enabled us to examine in detail critical small RNA features as size distribution, tissue-specific regulation and sequence conservation between different organs in this species. We also developed database resources and a dedicated website (http://smallrna.udel.edu/) with computational tools for allowing other users to identify new miRNAs or siRNAs involved in specific regulatory pathways, verify the degree of conservation of these sequences in other plant species and map small RNAs on genes or larger regions of the maize genome under study. Small RNA libraries were derived from leaves, flowers and fruit of Persea americana. Total RNA was isolated using the Plant RNA Purification Reagent (Invitrogen), and submitted to Illumina (Hayward, CA, http://www.illumina.com) for small RNA library construction using approaches described in (Lu et al., 2007) with minor modifications. The small RNA libraries were sequenced with the Sequencing-By-Synthesis (SBS) technology by Illumina. PERL scripts were designed to remove the adapter sequences and determine the abundance of each distinct small RNA. We thank Doug Soltis for providing the plant material as well as Kan Nobuta and Gayathri Mahalingam for assistance with the computational methods.