Ensete workshop with genomics data as part of GCRF BBSRC project lead by Royal Botanic Gardens Kew organized by Wolkite University, Addis Ababa Universities and others

1. Ensete genomics: diversity,
evolution and potential
Enhancing exploitation of the sustainable,
diverse Ethiopian starch crop
Presented by Pat Heslop-Harrison phh@molcyt.com
www.molcyt.org

2. International workshop and conference: Research on Enset and its Agri-system
Highlighting the outcomes and impact of research undertaken by the GCRF Enset, Enset
IFLIP and Enset Agri-systems project partners and collaborators funded by BBSRC-GCRF
Hosted by Wolkite University, Wolkite, SNNPR-Ethiopia in collaboration with Ethiopian
Biodiversity Institute, Addis Ababa University, Hawassa University, Leicester University
and RBG, Kew (UK)
February 10-11 2020
3rd Pathway Meeting towards the Enset Centre of Excellence (After Addis Ababa 2016,
Hawassa 2018)
Venue: Dessalegn Lodge

3. Some references!
Micronutrient composition and microbial community analysis across diverse landraces of the
Ethiopian orphan crop enset. Solomon Tamrata, James S. Borrell, Manosh K. Biswas, Dawd
Gashue, Tigist Wondimua, Carlos A. Vásquez-Londoñof, Pat J.S. Heslop-Harrison, Sebsebe
Demissew, Paul Wilkin and Melanie-Jayne R. Howes bioRxiv preprint posted online Nov. 8, 2019;
doi: http://dx.doi.org/10.1101/834564
Enset in Ethiopia: a poorly characterized but resilient starch staple. James S. Borrell, Manosh K.
Biswas, Mark Goodwin, Guy Blomme, Trude Schwarzacher, J. S. (Pat) Heslop-Harrison, Abebe M.
Wendawek, Admas Berhanu, Simon Kallow, Steven Janssens, Ermias L. Molla, Aaron P. Davis,
Feleke Woldeyes, Kathy Willis, Sebsebe Demissew and Paul Wilkin Annals of Botany 123: 747–
766, 2019. doi: http://dx.doi.org/10.1093/aob/mcy214
www.ensete-project.org

4. International workshop and conference:
Research on Enset and its Agri-system
Highlighting outcomes and impact of research undertaken by
the GCRF Enset, Enset IFLIP and Enset Agri-systems project
partners and collaborators funded by BBSRC-GCRF
Hosted by Wolkite University, Wolkite, SNNPR-Ethiopia in
collaboration with Ethiopian Biodiversity Institute, Addis
Ababa University, Hawassa University, Leicester University and
RBG, Kew (UK)
3rd Pathway Meeting towards the Enset Centre of Excellence
(After Addis Ababa 2016, Hawassa 2018)
Manosh Biswas

6. Agronomy
G&A
Genetics

7. • GBS – genotyping by sequencing
• Pathology
• Food processing
• Genome-wide SSR
• Medicinal enset diversity
• Website & outreach

8. GBS – Genotyping By Sequencing protocol
Measures all the genetic variation
How different are cultivars? And wild accessions?
Which genetic variants link to agronomic traits,
geography, disease & abiotic stress resistance, yield
& quality traits? Breeding for now & the future.
Sequencing outsourced to

9. 113,075 SNP sites genotyped in at least 50%
of the samples, each with average of 34 tGBS
reads/SNP/genotyped sample

10. Genetic diversity and population structure of wild and cultivated Ensete collected all over the Ethiopia
K=3
Admixture model

11. Genetic diversity and population structure of wild and cultivated Ensete collected all over the Ethiopia
1 851Chamo 36 357Gimbowa 71 254Yesherakinke 106 640Shallakuma 141 110Haqudhaa 176 338Borcho 211 824Sassa 246 909Wild_909
2 488Worsaife 37 364Guadamerat 72 316Zoober 107 607Dimoye 142 354Adoyo 177 237Bullo 212 563Sedisso 247 910Wild_910
3 895Arooko 38 329Guadbadadet 73 409Badadet 108 694Genna_red 143 374kake 178 169Buserate 213 698Separa 248 10
4 913Un_green 39 259Guariye 74 408Ferezye 109 380Ganticha 144 501Gishira 179 840Chamesa 214 841Sinayso 249 883wild_883
5 914Un_red 40 118Horate 75 417Nechwe 110 105Kulle 145 590Fuga 180 834Chamo 215 466Siskela 250 887wild_887
6 384Ganticha 41 152Inniba 76 5Pop1 111 682Maziya 146 622Badadiya 181 449Feleke 216 319Tagadet 251 437wild_437
7 604Toracho 42 265Jobra 77 201Pop2 112 684Bole 147 651Mato 182 695Genna_white 217 79Dare 252 465Disease_furtiye
8 683Wanade 43 122Kekeso 78 202Pop2 113 633Katane 148 504Moche 183 112Haho 218 911Un_green 253 409Disease_wilt
9 162Achachet 44 326Lemad 79 203Pop2 114 644Nakaka 149 372Qorqore 184 843Halako 219 467Yefurenzir 254 414Disease_wilt
10 153Achora 45 234Lemat 80 210Pop3 115 393Agena_red 150 658Sirrere 185 15wild_000015 220 912Un_red 255 424Disease_wilt
11 297Agade 46 178Lemat 81 211Pop3 116 268Agena_white 151 396Tassa 186 439Separa 221 553Un_red 256 436Lemat
12 149Amerat 47 32Lemat 82 212Pop3 117 649Ankogenna 152 341Shawe 187 109Botate 222 554Un_green
13 315Anhauriye 48 293Moyete 83 12Pop4 118 593Dinke 153 355Medasho 188 182Hambat 223 490Worsaife
14 298Ankafuye 49 36Nechisedi 84 260Yekeswa 119 395Dirbo 154 548Islama 189 348Hekeche 224 681Dumo
15 292Astara 50 303Nechwe 85 164Gare 120 350Ganticha 155 639Bundua 190 479Balaka 225 831Gopo
16 188Awugne 51 138Nechwe 86 221Bore 121 387Dishira 156 522Bowe_addo 191 867Akatonke 226 871Kokazo
17 220Badadet 52 288Nechwe 87 78Kekar 122 654Fello 157 635Banga 192 829Ambaro 227 877Oysie
18 198Badadet 53 299Orate 88 404Disease_sample 123 343Gadime 158 645Hoye 193 480Lekaka 228 849Chade
19 25Badadet 54 93Qeso 89 405Disease_sample 124 605Harame 159 626Suitye 194 267Lemicho 229 468Kenbatiy
20 40Bashalga 55 200Qore 90 406Disease_sample 125 662Silkante 160 345Feral_red 195 487Liso 230 337Awolcho
21 358Bazariya 56 287Quashquashye 91 586Derassiado 126 129Adara 161 344Feral_green 196 844Mallo 231 111Benjo
22 144Bishaganchwe 57 84Quiminar 92 386Birbo 127 235Askala 162 491Mandaloka 197 442Deree 232 823Bonozo
23 295Bishamerat 58 28Sebara 93 339Birra 128 642Chichia 163 620Gefetano 198 491Mandaloka 233 302Bua
24 363Bishastara 59 285Separa 94 591Toracho 129 373Dambale 164 397Kiticho 199 813Massa 234 128Bullancho
25 307Busara 60 308Shertiye 95 130Huwisho 130 275Gullumo 165 508Madicha 200 452Maze 235 842Bundo
26 155Chachata 61 90Shifere 96 621Arke 131 385Ado 166 438Tetteret 201 623Maze 236 826Charga
27 191Dere 62 39Tatarata 97 103Genna 132 106Kanko 167 440Badadet 202 850Maze 237 524Hankona
28 81Dima 63 168Teganen 98 580Gulumo 133 631Lembo 168 324Abakita 203 864Mazia 238 588Chacho
29 135Dinkinet 64 311Tereriye 99 615Nifo 134 546Loji 169 471Abat_merza 204 282Mundarare 239 602Astara
30 309Edemert 65 159Umbati 100 624Touzoma 135 563Sedisso 170 516Ado 205 893Nobo 240 469Fereziye
31 291Emeriye 66 139Usmail 101 519Damala 136 108Torora 171 243Ado 206 460Oniya 241 518Ganticha
32 26Ferezye 67 172Waka 102 101Gussalo 137 550Adenona 172 881Anchero 207 369Orete 242 277Torora
33 151Ferezye 68 312Wanadiye 103 619Halle 138 533Alaticho 173 505Argama 208 441Agade 243 892Awugne
34 179Ferezye 69 42Worke dima 104 556Chacho 139 376Filila 174 244Beresey 209 838Pelo 244 140Guariye
35 117Ganchwe 70 284Yegondiye 105 589Dowiramo 140 351Medasho 175 852Boda 210 701Borbodicho 245 227Yeshifere

12. Genetic diversity and population structure of wild and cultivated Ensete collected all over the Ethiopia
All result to be place here before Kew meeting……………………………..
K=6
Admixture model

13. 0
2000000
4000000
1
187
373
559
745
931
1117
1303
1489
1675
1861
2047
2233
2419
2605
2791
2977
3163
3349
3535
3721
3907
4093
4279
4465
Erwinia amylovora vs P1EN079
0
2000000
4000000
1
63
125
187
249
311
373
435
497
559
621
683
745
807
869
931
993
1055
1117
1179
1241
1303
1365
1427
1489
1551
1613
Erwinia amylovora vs P1EN082
0
5000000
1 4 7 101316192225283134374043464952555861646770737679
Erwinia amylovora VS P1EN099
0
5000000
1
78
155
232
309
386
463
540
617
694
771
848
925
1002
1079
1156
1233
1310
1387
1464
1541
1618
1695
1772
1849
Erwinia amylovora VS P1EN100
0
2000000
4000000
1
218
435
652
869
1086
1303
1520
1737
1954
2171
2388
2605
2822
3039
3256
3473
3690
3907
4124
4341
4558
4775
4992
Erwinia amylovora vs P1EN101
0
5000000
1
76
151
226
301
376
451
526
601
676
751
826
901
976
1051
1126
1201
1276
1351
1426
1501
1576
1651
1726
1801
1876
Erwinia amylovora vs P1EN102
Hit count
Hit count
Hitposition(bp)
Hitposition(bp)
0
5000000
1
7
13
19
25
31
37
43
49
55
61
67
73
79
85
91
97
103
109
115
121
127
133
FOC4 vs En082
0
2000000
4000000
1
11
21
31
41
51
61
71
81
91
101
111
121
131
141
151
161
171
181
191
201
211
221
231
241
FOC4 vs En100
0
5000000
10000000
1
91
181
271
361
451
541
631
721
811
901
991
1081
1171
1261
1351
1441
1531
1621
1711
1801
1891
1981
2071
2161
FOC4 vs En101
0
1000000
2000000
3000000
1
79
157
235
313
391
469
547
625
703
781
859
937
1015
1093
1171
1249
1327
1405
1483
1561
1639
1717
1795
1873
1951FOC4 vs En079
Hitposition(bp)
Hitposition(bp)
Disease sample tGBS
reads aligned against
Musaceae pathogen
genomes: mostly 16S
rRNA genes

14. Disease sample raw reads align against whole
genome of Xanthomonas sp. Blast hit
distribution and genome coverage.
BacterialgenomeHitposition(bp)
Hit count

15. Microbial community in kocho fermentation
Acetobacter, Lactobacillus and Bifidobacterium predominate
Microbial fermentation improves digestibility, quality or safety
Impacts food security and public health

16. Microbial community in kocho fermentation
Acetobacter, Lactobacillus and Bifidobacterium predominate
Microbial fermentation improves digestibility, quality or safety
Impacts food security and public health

17. • Germplasm: Bizuayehu Tesfaye, Hawassa, Ethiopia

18. Comprehensive landscaping of microsatellite in Enset (Ensete ventricosum) genome and web-based marker resource development
PCR profile for 48 enset landraces by three EMM markers. (M: Hyper Ladder 1; lane 1-48 enset
landraces; lane 49 and 50 as control use Enset sp and Musa sp )
4% Agarose gel

19. Comprehensive landscaping of microsatellite in Enset (Ensete ventricosum) genome and web-based marker resource development
Comparative microsatellite frequency distribution in four Ensete ventricosum genomes. (a)motif type
distribution, (b) motif class (Class I >20 bp and Class II ≤20 bp) distributions,

20. Distribution of mono-hexa nucleotide repeat motifs.

21. Comprehensive landscaping of microsatellite in Enset (Ensete ventricosum) genome and web-based marker resource development

22. Comprehensive landscaping of microsatellite in Enset (Ensete ventricosum) genome and web-based marker resource development
Bedadeti Derea JungleSeeds Onjamo Over all
No of SSR 105347 93180 115315 97338 411180
Primer modelling successful 68559 52570 51844 55699 228672
% of primer modelling success 65 56 45 57 56
Non redundant primers 61958 49258 47399 51789
210404
(154586)*
% Of redundant primers 10 6 9 7 27
No of polymorphic markers (in silico) 41531 36923 33047 38284 37446
No of transferable markers (in silico) 52112 46305 36979 48369 45941
Primer modelling and in silico characterization
Number of unique primer pairs

23. 34 Poly, expected
band
40 pairs of unique
116 Pairs Primer
Comprehensive landscaping of microsatellite in Enset (Ensete ventricosum) genome and web-based marker resource development
PCR profile of the 15 EnSSR markers from their wet-lab validation.
101586
non-redundant primer
Filter
1. non annotated
2. Transferable less than 95%
clustered based on their
functions/or gene
PCR analysis

24. Comprehensive landscaping of microsatellite in Enset (Ensete ventricosum) genome and web-based marker resource development

25. Comprehensive landscaping of microsatellite in Enset (Ensete ventricosum) genome and web-based marker resource development
Common and specific EMM markers in
(a) enset cultivars and
(b) Musa species.

26. PCoA2
PCoA1
Principal Coordinates (PCoA)
medicinal
nonmedicinal
medicinal
nonmedicinal
Genetic diversity of enset (Ensete
ventricosum) landraces traditional
medicine using SSR markers.
Gizachew Woldesenbet Nuraga1

27. http://enset-project.org/

28. Home page
Research News & Events PartnersResources
Information db
Literature db
Gene db
Tandem repat
Molecular marker
Diversity db
Transposable
Transcription Factor
About Us
Marker search results
TR search results
TF search results
Figure 1. Feature diagram showing the overall functionalities of Ensete Knowledgebase (EKB). Screenshots of EKB web pages with five distinct features accessible from the navigation bar on
top: resources, research, news & events, partners and about us. List of the eight databases are listed as sub-menu in resources. Enset Information Data Base; Enset Diversity Data Base;
Enset Literature Data Base; Enset Tandem Repeats Data Base; Enset Gene Data Base; Enset Transcription Factor Data Base; Enset Transposable Element Data Base; Enset Molecular Marker
Data Base.
http://enset-project.org/index.html

29. Ensete knowledge base: a comprehensive database fill the knowledge gap of Ethiopian starch crop Ensete as well as model for other plant
species.
Figure: Architecture of Enset information database
(EnIfo@base)
Figure: Architecture of Enset literature database
(EnLit@base)
Architecture of Other 6 data base not shown here

31. http://enset-project.org/EKB_Research.html

32. http://enset-project.org/EKB_NewsEvent.html

33. i) assess Ensete genetic diversity
ii) conserve the Ensete gene pool
iii) identify pathogens and soil biota
iv) compare Ensete genome and other species
iv) apply genomics tools and tissue culture to
support breeding and use biodiversity
v) document and make information accessible.

35. Dr Mark Goodwin (9th August 1960 - 25th August 2018)

36. Jack Heslop-Harrison
10 February 1920 – 8 May 1998

38. Genetics & Genomics Resources Development to Enhance Exploitation Ethiopian Starch Crop Enset
for Support Livelihoods
•Distribution central, eastern & southern
Africa Only domesticated in Ethiopia. ~ 500
varieties, starch source 20 million people,
supplies fibres, medicines, animal
fodder & staple food source
➢Little known about
➢Genetics,
➢Genome,
➢Diversity.
➢Huge knowledge gaps
➢Minimal research
➢We developed
➢ Fill critical knowledge gap Enset
➢ Develop a online genomic
resources molecular marker,
genotypic Phenotypic information
➢ Model of other plant species
http://enset-project.org/

39. Enset genetic diversity is secured, valued and used
to support livelihoods through sustainable
production and improved food and nutrition
security.
• i) assess Ensete genetic diversity
• ii) conserve the Ensete gene pool
• iii) identify pathogens and soil biota
• iv) compare Ensete genome and other species
• iv) apply genomics tools and tissue culture to
support breeding and use biodiversity
• v) document and make information accessible.

40. http://enset-project.org/
Presented by Pat Heslop-Harrison phh@molcyt.com phh4@le.ac.uk

41. Ensete ventricosum 2nd genus in Musaceae
enset, ensete, false banana

42. ~1.5cm
Genome-wide profiling, landscaping and comparison of Repetitive Elements diversity in Ensete spp.
Work flow for best chromosome preparation for Enset spp.
1. Trim old root
2. Add potting mixture
3. Watering properly (every 2days)
4. Harvest root after 2 to 3 weeks
After 2 weeks of
trim
and watering
Before Re Potting Harvest
~1.5 cm root
Root preserved
3:1 (Ethanol:
Acetic acid)
Incubate in
Hydroxyquinoline
24h (4h RT+20h 4C)
Root wash in
water
Chromosome preparation and fluorescent analysis carried out
following the protocol developed by Dr. Trude Schwarzacher (2016)
References: Schwarzacher T. Preparation and fluorescent analysis of plant
metaphase chromosomes. InPlant Cell Division 2016 (pp. 87-103). Humana Press,
New York, NY.

43. Wash 5min in
1X Enzyme
buffer
Further wash
5min in 1X
Enzyme buffer
Incubate in
Enzyme at 37C for
180min
Incubate in 1X
Enzyme buffer
4C for 48 to72h
Genome-wide profiling, landscaping and comparison of Repetitive Elements diversity in Ensete spp.
Work flow for best chromosome preparation for Enset spp.
Perfectly digested root
Enzyme solution 37C 180min
Enzyme buffer 48h
Metaphase
2n=18
Chromosomes
Protocol:SchwarzacherT.(2016)

44. Root
Harvest
time
Enzyme
solution
Digestion
time
Incubation 4°
with enzyme
buffer
9:00am ¼ strength 30min 24h
9:30am ½ strength 60min 48h
10:00am Full strength 90min 72h
10:30am 120min 96h
11:00am 150min
11:30am 180min
12:00am 210min
Genome-wide profiling, landscaping and comparison of Repetitive Elements diversity in Ensete spp.
Methods standardization for chromosome preparations
Root Harvest month
12/12/2018 December
05/02/2019 February
11/02/2019 February
21/05/2019 May
01/06/2019 June

45. Genome-wide profiling, landscaping and comparison of Repetitive Elements diversity in Ensete spp.
Early prophase Early metaphase
or pro-metaphase
Metaphase
2n=18 chromosomes
DAPI staining of Ensete ventricosum chromosomes (2n=18)
Protocol:SchwarzacherT.(2016)

46. Genome-wide profiling, landscaping and comparison of Repetitive Elements diversity in Ensete spp.
(a) Ensete ventricosum mitotic metaphase. In situ hybridization with 18S (green) and 5S (red) probe.
(b) Karyotype analysis of Ensete ventricosum based on the size and signal patterns.
a
b
Two major and one minor pairs of 18S rDNA
One pair of 5S rDNA
Protocol:SchwarzacherT.(2016)

47. Genetics & Genomics Resources Development to Enhance Exploitation Ethiopian
Starch Crop Enset for Support Livelihoods [Dr. Manosh K Biswas ]
Out come from this project:
Fill critical knowledge gap Enset
Develop a online genomic resources
molecular marker, genotypic
Phenotypic information
Model for other plant species
➢Little known about Enset: Genetics, Genomics and Population Diversity. http://enset-project.org/
Funded by: Research Partners:

48. Genomics changes study of
taxonomy, phylogeny, diversity
Revolutionizes crop genetics
and breeding
Exploits Musa as a reference
i) assess Ensete genetic diversity
ii) conserve the Ensete gene pool
iii) identify pathogens and soil biota
iv) compare Ensete genome and other
iv) apply genomics tools and tissue cult
support breeding and use biodiversity
v) document and make information acc

49. 1000 bp
800 bp
Azhar M, Heslop-Harrison JS. Genomes,
diversity and resistance gene analogues in
Musa species. Cytogenetic and genome
research. 2008 May 7;121(1):59-66.
i) assess Ensete genetic diversity
ii) conserve the Ensete gene pool
iii) identify pathogens and soil biota
iv) compare Ensete genome and other species
iv) apply genomics tools and tissue culture to
support breeding and use biodiversity
v) document and make information accessible.

50. Ensete ventricosum
‘Maurelli’ 2n=18
5S rDNA 5S rDNA (AAC)7

51. The Global Musa Genomics
Consortium
• To assure the
sustainability of banana
as a staple food crop by
developing an integrated
genetic and genomic
understanding, allowing
targeted breeding,
transformation and
more efficient use of
Musa biodiversity

52. • Vision: Musa genetic diversity is secured,
valued and used to support livelihoods
through sustainable production and improved
food and nutrition security.
• Actions aim to i) assess Musa genetic
diversity, ii) conserve the entire Musa gene
pool, iii) maximize use of genetic diversity, iv)
apply genomics tools to banana to better
support breeding and v) document and make
information accessible.

53. Genomics changes study of
taxonomy, phylogeny, diversity
Revolutionizes crop genetics
and breeding
Exploits Musa as a reference