1 / 25

RICE PHYLOGENY REVISITED

RICE PHYLOGENY REVISITED. N. K H I R I P E T AND V. POTLURI. Some Background. Rice is staple for more than half of the world’s population Large collection of germplasm [ >10000 accessions] held at IRRI Plant breeders/genecists use these to develop news cultivars

lula
Download Presentation

RICE PHYLOGENY REVISITED

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. RICE PHYLOGENY REVISITED N. K H I R I P E TAND V. POTLURI

  2. Some Background • Rice is staple for more than half of the world’s population • Large collection of germplasm [ >10000 accessions] held at IRRI • Plant breeders/genecists use these to develop news cultivars • For this purpose, evolutionary history/phylogeny is important

  3. Rice genetics • Rice is usually a diploid, but tetraploids are not uncommon • The diploid genome is classified as • AA,BB,CC,DD,EE,FF,GG,HH.KK • The tetraploids are mostly allo • BBCC,CCDD,HHJJ,HHKK

  4. Taxa in the Genus Oryza: the species and genome groups • Table 1-1.  Taxa in the genus Oryza:  the species and genome groups. [From IRRI] • Species2nGenomeDistribution • Sect. OryzaSer. Sativae • O. barthii  24 AA Sub-Saharan Africa • O. glaberrima 24 AA West Africa • O. glumaepatula  24 AA South, Central America • O. longistaminata  24 AA Sub-Saharan Africa • O. meridionalis  24 AA Tropical Australia • O. nivara 24 AA Tropical, Subtropical Asia • O. rufipogon  24 AA Tropical, Subtropical Asia, Tropical Australia • O. sativa 24 AA Worldwide • Ser. Latifoliae • O. eichingeri 24 CC South Asia, East Africa • O. alta  48 CCDD South, Central America • O. grandiglumis 48 CCDD South, Central America • O. latifolia 48 CCDD South, Central America • O. minuta 48 BBCC Philippines, Papua New Guinea • O. punctata 24, 48 BB, BBCC Sub-Saharan Africa • O. rhizomatis 24 CC Sri Lanka • O. officinalis 24,48 CC, BBCC Tropical, Subtropical Asia • Ser. Australienses • O. australiensis 24 EE ropical Australia • Sect. BrachyanthaSer. Brachyanthae • O. brachyantha 24 FF Sub-Saharan Africa • Sect. PadiaSer. Meyerianae • O. granulata  24 GG South, Southeast Asia • O. meyeriana 24 GG Southeast Asia • O. neocaledonica 24 ?? New Caledonia • Ser. Ridleyanae • O. longiglumis 48 HHJJ Indonesia (Irian Jaya), Papua New Guinea • O. ridleyi 48HHJJSoutheast Asia • Ser. Schlechterianae • O. schlechteri 48 HHKK Indonesia (Irian Jaya), Papua New Guinea

  5. So, What is the Problem? • No problem really, but • We would like to have a better tool to understand the interrelationships of various cultivars • Which in turn should help breeders and genecists

  6. Well then, what is the plan? • We chose four important enzymes, viz • Maturase • Integrase • Alcohol dehydrogenase I and • Alcohol dehydrogenase II

  7. Then, • We got the protein sequence data [from NCBI]for these enzymes for 8 cultivars O. sativa 24 AA Worldwide • Ser. Latifoliae • O. eichingeri 24 CC South Asia, East Africa • O. alta  48 CCDD South, Central America • O. grandiglumis 48 CCDD South, C. America • O. latifolia 48 CCDD South, C.America • O. minuta 48 BBCC Philippines, PN G • O. punctata 24, 48 BB, BBCC Sub-Saharan Africa • O. rhizomatis 24 CC Sri Lanka

  8. Hold On • Change of Speaker

  9. Methods [contd.] • We constructed a phylogenetic tree for each enzyme using Workbench using Clustalw • We calculated the distance matrix from this tree using ClustalDist

  10. [Methods-contd.] • We converted the distance matrix to digital form to be used in JBenzer and GDEusing PERL scripts. • Threshold • We used a median point between the distance values as a threshold. We will discuss the implications of changing the threshold after presenting the results

  11. Finally [methods contd.] • We combined all the distance matrices and combined in to one matrix and • Digitized the matrix for use in JBenzer and GDE to obtain a single Benzer plot

  12. Biology Workbench clustalw clustdist clustdist2benzer.pl sequences benzer2gde.pl

  13. Clustdist2benzer.pl OL (1) 0.000 0.002 0.002 0.008 0.006 0.013 0.015 0.015 OG (2) 0.002 0.000 0.000 0.006 0.004 0.012 0.013 0.013 OA (3) 0.002 0.000 0.000 0.006 0.004 0.012 0.013 0.013 OE (4) 0.008 0.006 0.006 0.000 0.002 0.013 0.015 0.015 OR (5) 0.006 0.004 0.004 0.002 0.000 0.012 0.013 0.013 OS (6) 0.013 0.012 0.012 0.013 0.012 0.000 0.015 0.015 OP (7) 0.015 0.013 0.013 0.015 0.013 0.015 0.000 0.000 OM (8) 0.015 0.013 0.013 0.015 0.013 0.015 0.000 0.000 JBENZER 8 1,1,1,0,0,0,0,0,OL 1,1,1,0,1,0,0,0,OG 1,1,1,0,1,0,0,0,OA 0,0,0,1,1,0,0,0,OE 0,1,1,1,1,0,0,0,OR 0,0,0,0,0,1,0,0,OS 0,0,0,0,0,0,1,1,OP 0,0,0,0,0,0,1,1,OM

  14. Benzer2gde.pl "OL","OG" "OL","OA" "OG","OL" "OG","OA" "OG","OR" "OA","OL" "OA","OG" "OA","OR" "OE","OR" "OR","OG" "OR","OA" "OR","OE" "OS","OS" "OP","OM" "OM","OP" JBENZER 8 1,1,1,0,0,0,0,0,OL 1,1,1,0,1,0,0,0,OG 1,1,1,0,1,0,0,0,OA 0,0,0,1,1,0,0,0,OE 0,1,1,1,1,0,0,0,OR 0,0,0,0,0,1,0,0,OS 0,0,0,0,0,0,1,1,OP 0,0,0,0,0,0,1,1,OM

  15. OL OG OA OE OR OS OP OM Maturase

  16. OA OG OL OS OP OE OR OM Integrase

  17. OP OA OG OS OR OE OL OM Alcohol dehydrogenase I

  18. Alcohol dehydrogenase II OL OG OA OM OP OS OE OR

  19. Combined Matrix

  20. Back to the Beginning

  21. Conclusions • The phylogenetic trees and JBenzer differ in some respects • JBenjer plots show O.sativa [2n=24,AA]to be unique but in phylogenic trees,it is clustered with O.punctata [4x,48,BBCC] or O.grandiglumis and O.alta[4x,48,CCDD]

  22. BUT • Remember the threshold values? • We used a median value from a matrix table and it does give relationships which can be related to their genomes. • IF we change the threshold value, the Benjer plot will change which brings the question whether relationships based on distance matrices need re-visitation

  23. We realize that phylogenetic trees based on distance matrices have been used for so long • However, different scientists calculate and interpret the distance matrix results differently • Does it help if the input data is obtained differently from the beginning in binary format

  24. We used a very limited data to compare but it does indicate that we may have to look at the phylogenetic relationships using improved methods to minimize and /or to understand better varied interpretations

  25. Finally • A Gigabyte of Thanks to • ALL THE BIOQUEST STAFF AND THE PARTICIPANTS OF THIS WORKSHOP WHO MADE OUR PARTICIPATION IN THE WORKSHOP A MEMORABLE AND REWARDING EXPERIENCE

More Related