bioRxivPlant Biology
Elucidating the unknown transcriptional responses and PHR1 mediated biotic and abiotic stress tolerance during phosphorus-limitation
W. R. Scheible, P. Pandey-Pant, B. D. Pant, N. Krom, R. D. Allen, K. S. Mysore
Abstract
Phosphorus (P) limitation in the majority of world soils is a major constraint for plant growth and crop productivity. RNA sequencing was used to discover novel P-responsive gene transcripts (PRGT) in leaves and roots of Arabidopsis. Hisat StringTie and Cufflinks TopHat transcript assembler were used to analyze reads and identify 1,074 PRGTs with a >5-fold altered abundance during P-limitation. Interestingly, 60% of these transcripts were not previously reported. Among the novel PRGT, 106 were from unannotated genes, and some were among the most P-responsive, including At2g36727 which encodes a novel microRNA. Annotated novel PRGTs encode for transcription factors, microRNAs, small signaling peptides, long non-coding RNAs, defense-related proteins, and transporters, along with proteins involved in many biological processes. We identified several genes that undergo alternative splicing during P-limitation, including a novel miR399 resistant splice variant of PHOSPHATE2 (PHO2.2). Several novel P-responsive genes were regulated by PHOSPHATE STARVATION RESPONSE1 (PHR1), PHR1-LIKE 1 (PHL1) and PHO2. We discovered that P-limited plants show increased resistance to pathogens and drought stress mediated by PHR1-PHL1. Identification of novel P-responsive transcripts and the discovery of the influence of P-limitation on biotic and abiotic stress adds a significant component to our understanding of plant P-signaling. HighlightPhosphorus limitation elicits the expression of several novel genes including many previously unannotated genes, noncoding RNAs, small peptides and alternatively spliced RNAs, and leads to enhanced disease and drought tolerance.
- organism: Arabidopsis
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- research focus: differential expression
- approach: statistical model
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