TITLE: Genetic mechanisms associated with floral initiation and the repressive effect of fruit on flowering in apple (Malus x domestica Borkh.)
AUTHORS: Chris Gottschalk, Songwen Zhang, Phil Schwallier, Sean Rogers, M. John Bukovac, Steve van Nocker

[DESCRIPTION]
<div class = "text-blocks"><div class = "text-block"><span>Many apple cultivars are subject to biennial fluctuations in flowering and fruiting. It is believed that this phenomenon is caused by a repressive effect of developing fruit on the initiation of flowers in the apex of proximal bourse shoots. However, the genetic pathways of floral initiation are incompletely described in apple, and the biological nature of floral repression by fruit is currently unknown. In this study, we characterized the transcriptional landscape of bourse shoot apices in the biennial cultivar, 'Honeycrisp', during the period of floral initiation, in trees bearing a high fruit load and in trees without fruit. Trees with high fruit load produced almost exclusively vegetative growth in the subsequent year, whereas the trees without fruit produced flowers on the majority of the potential flowering nodes. Using RNA-based sequence data, we documented gene expression at high resolution, identifying >11,000 transcripts that had not been previously annotated, and characterized expression profiles associated with vegetative growth and flowering. We also conducted a census of genes related to known flowering genes, organized the phylogenetic and syntenic relationships of these genes, and compared expression among homeologs. Several genes closely related to </span><span style = "font-style:italic;">AP1, FT, FUL, LFY,</span><span> and </span><span style = "font-style:italic;">SPLs </span><span>were more strongly expressed in apices from non-bearing, floral-determined trees, consistent with their presumed floral-promotive roles. In contrast, a homolog of </span><span style = "font-style:italic;">TFL1</span><span> exhibited strong and persistent up-regulation only in apices from bearing, vegetative-determined trees, suggesting a role in floral repression. Additionally, we identified four </span><span style = "font-style:italic;">Gibberellic Acid (GA) 2 oxidase </span><span>genes that were expressed to relatively high levels in apices from bearing trees. These results define the flowering-related transcriptional landscape in apple, and strongly support previous studies implicating both gibberellins and </span><span style = "font-style:italic;">TFL1</span><span> as key components in repression of flowering by fruit.</span></div></div>

[STEPS]
?. [Read Alignment]
Retrieve RNAseq librariesFiles are locally maintained but can be retrieved from NCBI SRA database
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Filter RNAseq reads for quality and removal of the adapter sequences
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Align RNAseq reads to reference genome assembly
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Convert SAM alignment files into binary format and sort
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Assembly of transcripts and annotation of individual transcriptomes
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Assembling merged transcriptome
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Calculate transcript abundance
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Perform DEG analysis
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Retrieve transcript FASTA sequences
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Identify homologous peptide sequences between Honeycrisp/Apple and Arabidopsis
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Quality assessment of the transcriptome assembly
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Predicting coding potential of assembled transcripts
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Predicting coding potential using CPC2
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Predicting coding potential using PLEK
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Predicting coding potential using CPAT
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Phylogentics of target genes
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Predicting coding sequences of target transcripts identified by blast homology
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Reciprocal blast to identify high confidence homologs of flowering genes
This was done using in-house scripts. If interested please contact Steve van Nocker @ vannocke@msu.edu
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Assembly of transcripts from reads that failed to map to the reference genome
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Construct gene and isoform models
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Create index using de novo transcripts
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Index the reference genome fasta using HISAT2
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Download reference genome Source:
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Alignment of unmapped reads
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Sort the alignments
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Quantify expression per unmapped read library using cuffquant
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Retrieve normalized expression data
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Assigning annotation using BLAST from various databases
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TAIR10 Arabidopsis annotation
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Model longest ORFs and predict representative transcripts from de novo transcript dataset
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Normalize the quantified expression
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Syntenic Analysis
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