A new reference genome for Sorghum bicolor reveals high levels of sequence similarity between sweet and grain genotypes: implications for the genetics of sugar metabolism.
Gene expression
Genomics
Sorghum
Sugar metabolism
Sugar transport
Journal
BMC genomics
ISSN: 1471-2164
Titre abrégé: BMC Genomics
Pays: England
ID NLM: 100965258
Informations de publication
Date de publication:
27 May 2019
27 May 2019
Historique:
received:
25
07
2018
accepted:
24
04
2019
entrez:
29
5
2019
pubmed:
28
5
2019
medline:
13
9
2019
Statut:
epublish
Résumé
The process of crop domestication often consists of two stages: initial domestication, where the wild species is first cultivated by humans, followed by diversification, when the domesticated species are subsequently adapted to more environments and specialized uses. Selective pressure to increase sugar accumulation in certain varieties of the cereal crop Sorghum bicolor is an excellent example of the latter; this has resulted in pronounced phenotypic divergence between sweet and grain-type sorghums, but the genetic mechanisms underlying these differences remain poorly understood. Here we present a new reference genome based on an archetypal sweet sorghum line and compare it to the current grain sorghum reference, revealing a high rate of nonsynonymous and potential loss of function mutations, but few changes in gene content or overall genome structure. We also use comparative transcriptomics to highlight changes in gene expression correlated with high stalk sugar content and show that changes in the activity and possibly localization of transporters, along with the timing of sugar metabolism play a critical role in the sweet phenotype. The high level of genomic similarity between sweet and grain sorghum reflects their historical relatedness, rather than their current phenotypic differences, but we find key changes in signaling molecules and transcriptional regulators that represent new candidates for understanding and improving sugar metabolism in this important crop.
Sections du résumé
BACKGROUND
BACKGROUND
The process of crop domestication often consists of two stages: initial domestication, where the wild species is first cultivated by humans, followed by diversification, when the domesticated species are subsequently adapted to more environments and specialized uses. Selective pressure to increase sugar accumulation in certain varieties of the cereal crop Sorghum bicolor is an excellent example of the latter; this has resulted in pronounced phenotypic divergence between sweet and grain-type sorghums, but the genetic mechanisms underlying these differences remain poorly understood.
RESULTS
RESULTS
Here we present a new reference genome based on an archetypal sweet sorghum line and compare it to the current grain sorghum reference, revealing a high rate of nonsynonymous and potential loss of function mutations, but few changes in gene content or overall genome structure. We also use comparative transcriptomics to highlight changes in gene expression correlated with high stalk sugar content and show that changes in the activity and possibly localization of transporters, along with the timing of sugar metabolism play a critical role in the sweet phenotype.
CONCLUSIONS
CONCLUSIONS
The high level of genomic similarity between sweet and grain sorghum reflects their historical relatedness, rather than their current phenotypic differences, but we find key changes in signaling molecules and transcriptional regulators that represent new candidates for understanding and improving sugar metabolism in this important crop.
Identifiants
pubmed: 31133004
doi: 10.1186/s12864-019-5734-x
pii: 10.1186/s12864-019-5734-x
pmc: PMC6537160
doi:
Substances chimiques
DNA, Plant
0
Sugars
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
420Subventions
Organisme : Office of Science
ID : DE-FG02-07ER64458
Organisme : Office of Science
ID : DE-AC02-05CH11231
Organisme : Office of Science
ID : DE-AR0000595
Références
Bioinformatics. 2015 Jan 15;31(2):166-9
pubmed: 25260700
Bioinformatics. 2014 Aug 1;30(15):2114-20
pubmed: 24695404
BMC Genomics. 2013 Sep 23;14:649
pubmed: 24059626
PLoS One. 2013 Jul 19;8(7):e68672
pubmed: 23904908
Trends Plant Sci. 2009 Apr;14(4):206-13
pubmed: 19285909
Bioinformatics. 2009 May 1;25(9):1105-11
pubmed: 19289445
Nat Methods. 2012 Mar 04;9(4):357-9
pubmed: 22388286
Fly (Austin). 2012 Apr-Jun;6(2):80-92
pubmed: 22728672
Genome Res. 2002 Apr;12(4):656-64
pubmed: 11932250
Front Plant Sci. 2013 Jun 26;4:223
pubmed: 23805151
Nat Rev Genet. 2011 May;12(5):363-76
pubmed: 21358748
Plant Cell. 2013 Jun;25(6):2253-64
pubmed: 23792371
Mol Plant. 2012 Jul;5(4):766-8
pubmed: 22815540
Theor Appl Genet. 2013 Aug;126(8):2051-64
pubmed: 23708149
Physiol Mol Biol Plants. 2013 Jul;19(3):307-21
pubmed: 24431500
Dev Cell. 2011 Dec 13;21(6):1116-28
pubmed: 22172674
Plant Signal Behav. 2016;11(1):e1117721
pubmed: 26619184
Genome Biol. 2011 Nov 21;12(11):R114
pubmed: 22104744
Nature. 2009 Jan 29;457(7229):551-6
pubmed: 19189423
Genome Biol. 2004;5(2):R12
pubmed: 14759262
Bioinformatics. 2006 Jul 1;22(13):1600-7
pubmed: 16606683
BMC Plant Biol. 2015 Jul 30;15:186
pubmed: 26223524
Genome Biol. 2011 Sep 14;12(9):R88
pubmed: 21917144
Proc Natl Acad Sci U S A. 2013 Jan 8;110(2):453-8
pubmed: 23267105
Arabidopsis Book. 2011;9:e0144
pubmed: 22303269
BMC Plant Biol. 2014 Sep 26;14:253
pubmed: 25928459
Nucleic Acids Res. 2003 Oct 1;31(19):5654-66
pubmed: 14500829
J Mol Biol. 1970 Mar;48(3):443-53
pubmed: 5420325
Plant J. 2018 Jan;93(2):338-354
pubmed: 29161754
Genome Biol. 2014;15(11):506
pubmed: 25468217
Plant J. 1999 Jun;18(5):541-50
pubmed: 10417704
Biotechnol Biofuels. 2016 Jun 17;9:127
pubmed: 27330561
Nat Genet. 2018 Feb;50(2):285-296
pubmed: 29358651
Plant Signal Behav. 2010 Jul;5(7):911-2
pubmed: 20523129
J Plant Physiol. 2012 Apr 15;169(6):605-13
pubmed: 22325624
Bioinformatics. 2015 Aug 15;31(16):2614-22
pubmed: 25847007
Plant Cell. 2014 Jan;26(1):121-35
pubmed: 24488960
Evol Bioinform Online. 2016 Jan 14;12:9-21
pubmed: 26792976
Funct Plant Biol. 2014 Sep;41(9):954-962
pubmed: 32481048
Plant Direct. 2018 Jul 23;2(7):e00070
pubmed: 31245734
Nat Methods. 2016 Dec;13(12):1050-1054
pubmed: 27749838
Bioinformatics. 2009 Aug 15;25(16):2078-9
pubmed: 19505943
Nat Methods. 2013 Jun;10(6):563-9
pubmed: 23644548
Curr Opin Plant Biol. 2015 Jun;25:53-62
pubmed: 25988582
BMC Plant Biol. 2007 Jun 20;7:33
pubmed: 17584916
Bioinformatics. 2016 Oct 1;32(19):3021-3
pubmed: 27318204
Front Plant Sci. 2016 Apr 21;7:474
pubmed: 27148302