Deep-sequencing microRNA profiling in Chrysanthemum morifolium tissues during flowering

O.A. Shulga1*

, A.V. Nedoluzhko2, A.V. Shchennikova

1, N.M. Gruzdeva

2, A.A. Shelenkov

3, F.S. Sharko

1, A.S. Sokolov

1, E.S. Pantiukh

4, S.M. Rastorguev

2, E.B. Prokhortchouk

2,4, K.G.

Skryabin1,2,4

1Institute of Bioengineering, Research Center of Biotechnology of the Russian Academy of Sciences, Leninsky Ave. 33, bld. 2, 119071, Moscow, Russia

2National Research Centre “Kurchatov Institute”, 1, bld. 140 Kurchatov Sq., Moscow, Russia, 123182

3Vavilov Institute of General Genetics, Russian Academy of Sciences, 3 Gubkina St., Moscow, Russia, 119991

4Faculty of Biology, Lomonosov Moscow State University, Leninskie gory 1-12, Moscow, Russia, 119234

*Corresponding author: email: shua2@yandex.ru; phone +7 499 1356219; fax +7 499 1350571

ESM_4 Supplementary Table S21 ‘Characteristics of precursors for the candidate novel and conserved miRNAs identified in C. morifolium’

Table S21 Characteristics of precursors for the candidate novel and conserved miRNAs identified in C. morifolium

cmo-

miRNA

miRNA sequence (5′ → 3′) L1 PL

2 MFE

4 AMFE

5 MFEI

6 GC% AU% U%

005 UUUCAUAUAUACCCAAACAUGC

ACUUUGGGUAUAUAUGAA*

22

18

76 -23.80 -31.32 1.13 27.63 72.37 35.52

007 AACCCGAUAACCCGAUAGU

UGUCGGCUUAUCGGGUCG*

19

18

91 -27.70 -30.44 0.73 41.76 58.24 25.27

008 UUUUUUUUUUAACGGGGUUU

UCCCCCGUUUAAAAAAAAAA*

20

20

77 -20.00 -25.97 0.95 27.27 72.73 42.86

009 GGUUCGGUCCUCGGUCC

AGACCGAACUGGACCGGACCA*

17

21

77 -39.90 -51.82 0.95 54.55 45.45 24.68

011 AACCCGUUUAACCUAUUC

AUGGGUUAGGUUUGGUU*

18

17

83 -22.70 -27.35 0.84 32.53 67.47 36.14

013 ACCGAAACCGGACCGGACC

GUUCGGUUCGUUUUUCGGUUU*

19

21

74 -31.40 -42.43 0.83 51.35 48.65 17.57

014 AAUUACAUAUAUCCCAA

GGGUAAAUAUGUAAUUUAU*

17

19

84 -21.40 -25.48 1.07 23.81 76.19 41.67

015 AAUUUCAUAUAUACCCAAAGUGCAA

GCAUGUUUGGGUAUAUAUGAAAUUG*

25

25

82 -28.60 -34.88 1.30 26.83 73.17 37.80

018 ACCACCAAAUGGCCUAG

AGGUGUGUACAUUUGGGGGUGG*

17

22

89 -37.40 -42.02 0.87 48.31 51.69 24.72

020 AAGGGUUCGAGUGUGACGCA

AUGCUCACACUCGAACCCUUCA*

20

22

70 -38.90 -55.57 0.95 58.57 41.43 21.43

024 UAAACCGGGUUUAAAAC

UUUCCAAACGGGUUUAGG*

17

18

69 -27.50 -39.86 0.79 50.72 49.28 27.54

025 GUACGGUUGGGUUGGUU

CGGACCGAACCGAACCG*

17

17

69 -30.40 -44.06 0.71 62.32 37.68 24.64

026 GGGGUGCACCGCCGACCGAC

UGAUUGGCGGGAUCCCCUU*

20

19

83 -42.60 -51.32 0.79 65.06 34.94 20.48

027 UUUCCAAACGGGUUAGG

CUAACUUUCGGGAAAAG*

17

17

80 -41.00 -51.25 0.95 53.75 46.25 22.50

028 CAAGGUGGAAAUUACUAAUAUACC

AAUAUCUAACAAUCUCCACCUUGAC*

24

25

65 -20.10 -30.92 0.77 40.00 60.00 26.15

031 AGUUAUCGGGUCGGGUU

CCUGAUAACCGAUAAUAAU*

17

19

66 -25.70 -38.94 0.89 43.94 56.06 31.82

032 UUUUUUUUUAAAAACCCCCCGGUU

GGGUUUUUUAAAAAAAA*

24

17

88 -35.80 -40.68 1.33 30.68 69.32 35.23

033 CGGUCCGUCGGUCCGCU

AGACCGAACUGGACCGGA*

17

18

73 -29.50 -40.41 0.76 53.42 46.58 24.66

039 UUUCCAAACGGGUUUAGGGGUU 22 81 -32.10 -39.63 0.75 53.09 46.91 24.69

ACCCUAAUUCGGGAAAGU* 18

045 CGGGGUAACCGGUAAACG

UUUCCGGGUAAACCGUU*

18

17

80 -29.10 -36.38 0.71 51.25 48.75 25.0

046 GUGUCUUACUUCAAAACUUAUAAGC

UCAUAAGUCUCGAAAUAAGCCACAA*

25

25

79 -21.00 -26.58 0.87 30.38 69.62 31.65

047 AGUACCAUGAACUAGGAAAUGU

UUUCAUAGUUCAGGUUACU*

22

19

86 -27.40 -31.86 0.69 46.51 53.49 26.74

048 GGAAGUAAAGUAAAGUAA

ACUUUAUUACUUACCU*

18

16

70 -21.50 -30.71 0.93 32.86 67.14 31.43

052 GUACGUACGUACGUACGUA

UGUGUCGUGUGUGUGUGUCGU*

19

21

77 -32.40 -42.08 0.98 42.86 57.14 35.06

053 UCAAGCUUUACCAAUCC

AGCUUGGCUUGAAAAGCUUGA*

17

21

77 -34.00 -44.15 1.13 38.96 61.04 29.87

060 ACCGAACCGAACCGAACCGAA

CGGUAACGGUAACGGUAACGGUAA*

21

24

66 -24.40 -36.97 0.68 54.55 45.45 7.58

062 AACCGAAACCAAACCGAAU

GUUGGUUUGGUUUUGGU*

19

17

76 -26.00 -34.21 1.83 31.58 68.42 46.05

065 CCCCGGGUAAAAAAAAACG

UUUUUUUUUAAACGGGGGG*

19

19

66 -22.80 -34.55 0.91 37.88 62.12 31.82

075 AAACCAAAAAACCAAACCAAAC

UUGGUCGUUACGUUGGUUUGG*

22

21

91 -26.70 -29.34 0.67 43.96 56.04 26.37

077 ACCGUGCACAAUAAGCCGAUGCUCU

AGCAUGGUAAUGUGCACGGAAA*

25

22

68 -24.70 -36.32 0.82 44.12 55.88 19.12

Average data for candidate novel mhy-miRNAs 77.1 ±

6.31

-28.88 ± 5.27 -37.58 ± 6.54 0.92 ± 0.16 43.35 ± 9.46 56.65 ± 9.46 27.71 ± 7.11

156bp UGCUCACUUCUCUUGCUGUCAAC

UGACAGAAGAGAGUGAGCAUA*

23

21

85

-47.80 -56.24 1.406 40.00 60.00 28.24

477 CAUCUCUCCCUCAAAGACUUCUG

AGUCUUUAGGGAGAGAUG*

23

18

66 -39.00 -59.09 1.30 45.45 54.55 28.79

6117 ACCCGAACCCGACCAACCCGACCCG

GUCGGGUUCGGGUAAAU*

25

17

67 -27.80 -41.49 0.77 53.73 46.27 23.88

6111.2 UGAGUUAUUAGUUCACA

CGUGAGAAUCUAAUGACUCUAGA*

17

23

81 -27.80 -34.32 0.84 40.74 59.26 34.57

Average data for known cmo-miRNAs 74.75 ±

8.25

-35.60 ± 7.80 -47.79 ± 9.88 1.08 ± 0.27 44.98 ± 4.61 55.02 ± 4.61 28.87 ± 2.85

Average data for plant miRNA (Zhang et al. 2006b) 144.57 ±

56.91

-65.06 ± 23.65 -45.93 ± 9.43 0.97 ± 0.19 47.92 ± 9.34 51.98 ± 9.41 28.56 ± 5.71

1 – miRNA/miRNA* length, nt; 2 – pre-miRNA length, nt; 3 – number of reads/ targets identified; 4 – minimal free energy, kcal/mol; 5 – minimal free energy of a 100-nt pre-miRNA =

(MFE/sequence length) x 100; 6 – minimal free energy index = AMFE /%GC content