Transcriptome profiling of developmental leaf senescence in sorghum (Sorghum bicolor)
Key message This piece of the submission is being sent via mail. Leaf senescence is essential for the nutrient economy of crops and is executed by so-called senescence-associated genes ( SAGs ). Here we explored the monocot C 4 model crop Sorghum bicolor for a holistic picture of SAG profiles by RNA...
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Veröffentlicht in: | Plant molecular biology 2016-11, Vol.92 (4-5), p.555-580 |
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Format: | Artikel |
Sprache: | eng |
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This piece of the submission is being sent via mail.
Leaf senescence is essential for the nutrient economy of crops and is executed by so-called senescence-associated genes (
SAGs
). Here we explored the monocot C
4
model crop
Sorghum bicolor
for a holistic picture of
SAG
profiles by RNA-seq. Leaf samples were collected at four stages during developmental senescence, and in total, 3396
SAGs
were identified, predominantly enriched in GO categories of metabolic processes and catalytic activities. These genes were enriched in 13 KEGG pathways, wherein flavonoid and phenylpropanoid biosynthesis and phenylalanine metabolism were overrepresented. Seven regions on Chromosomes 1, 4, 5 and 7 contained
SAG
‘hotspots’ of duplicated genes or members of cupin superfamily involved in manganese ion binding and nutrient reservoir activity. Forty-eight expression clusters were identified, and the candidate orthologues of the known important senescence transcription factors such as
ORE1, EIN3
and
WRKY53
showed “
SAG
” expression patterns, implicating their possible roles in regulating sorghum leaf senescence. Comparison of developmental senescence with salt- and dark- induced senescence allowed for the identification of 507 common
SAGs
, 1996 developmental specific
SAGs
as well as 176 potential markers for monitoring senescence in sorghum. Taken together, these data provide valuable resources for comparative genomics analyses of leaf senescence and potential targets for the manipulation of genetic improvement of
Sorghum bicolor
. |
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ISSN: | 0167-4412 1573-5028 |
DOI: | 10.1007/s11103-016-0532-1 |