Yi Capstone071604

Information about Yi Capstone071604

Published on December 7, 2007

Author: Waldarrama

Source: authorstream.com

Content

DNA sequence evolution in Sunflower and Lettuce:  DNA sequence evolution in Sunflower and Lettuce Yi Zou Thesis capstone report Major: Bioinformatics 07/16/2004 Advisor: Dr. Loren Rieseberg Dr. Sum Kim Background:  Background Sunflower and lettuce represent two major subfamilies of the Compositae Family, which is one of the largest and most diverse families of flowering plants Sunflower is an important oil seed crop and domestication and breeding have focused on seed traits. Lettuce is an important leaf crop and domestication and breeding have focused on leaf traits. Extensive lettuce and sunflower EST database available (CGPDB) Background:  Background Examination of DNA differences between closely related species of Compositae will provide insight into the nature of mutational rates and processes in this family Hypothesis: genes associated with primary domestication traits (seeds in sunflower and leaves in lettuce) will evolve faster than genes expressed in other tissues. Hypothesis: upstream enzymes in metabolic pathways will evolve less rapidly than downstream enzymes. Goals:  Goals Compare distribution of indels and base substitutions among closely related lettuce and sunflower EST sequences Compare rates of EST sequence divergence for genes from different tissue types Compare rates of EST sequence divergence from different pathway, and protein evolution among specific genes along major metabolic pathways Data:  Data http://cgpdb.ucdavis.edu CGPDB:  CGPDB contains about 112,000 individual ESTs sequenced from both sunflower and lettuce Sunflower: about 44,000 individual ESTs, previously assembled into 4430 unique contigs, were sequenced from two Helianthus annuus cultivars: RHA801(exotic) and RHA280(oil). Lettuce: around 68,000 ESTs, previously assembled into 8179 unique contigs(genes), sequenced from two species: Lactuca serriola (wild) and L. sativa (cultivated) Goals:  Goals Compare distribution of indels and base substitutions among closely related lettuce and sunflower EST sequences Compare rates of EST sequence divergence for genes from different tissue types and metabolic pathways Compare rates of EST sequence divergence from different pathway, and protein evolution among specific genes along major metabolic pathways Data Analysis – Example from sunflower:  Data Analysis – Example from sunflower Genotype 1 Genotype 2 Slide9:  Data Analysis –comparison of complete EST sequence Slide10:  Data Analysis – comparison of coding region only sun_vs_ath_TIGR_unique lettuce_vs_ath_TIGR_unique Slide11:  Result - Sequences information for assembling Contigs and conseneus Slide12:  Result – Comparison of complete EST sequences between two sunflower and two lettuce genotypes Slide13:  Result – Comparison of coding region only Slide14:  Conclusion1 Substitutions are 3-6 times more frequent than indels in both sunflower and lettuce, regardless of whether coding regions or complete EST sequences are analyzed. Goals:  Goals Compare distribution of indels and base substitutions among closely related lettuce and sunflower EST sequences Compare rates of EST sequence divergence for genes from different tissue types and metabolic pathways Compare rates of EST sequence divergence from different pathway, and protein evolution among specific genes along major metabolic pathways Data Analysis – EST divergence for different tissue types:  Data Analysis – EST divergence for different tissue types Lettuce: TAG0 - callus - "cls" TAG1 - roots - "rot" TAG2 - none (leaf) - "not" TAG3 - flowers pre-fert - "flr" TAG4 - flowers post-fert - "flo" TAG5 - chemical induction - "chi" TAG6 - none - "nos" TAG7 - roots env stress - "rts" TAG8 - shoots env stress - "shs" TAG9 - germinating seeds - "gsd" TAG10 - flowers env stress - "fls" TAG11 - leaves dark grow - "lvd Tag_1_7: all root related contigs Tag_3_4_10: All flower related contigs Tag_7_8_10: All contigs related to environment stress Sunflower: TAG0 - callus - "cls" TAG1 - roots - "rot" TAG2 - disk & ray flowers - "drf" TAG3 - flowers pre-fert - "flr" TAG4 - developing kernel - "dkn" TAG5 - chemical induction - "chi" TAG6 - none - "nos" TAG7 - roots env stress - "rts" TAG8 - shoots env stress - "shs" TAG9 - germinating seeds - "gsd" TAG10 - flowers env stress - "fls" TAG11 - hulls - "hls Tag_1_7: all root related contigs Tag_3_10: All contigs related to flower Tag_7_8_10: All contigs related to environment stress Slide17:  Result – number of tissue-specific contigs in sunflower Slide18:  Result – number of tissue-specific contigs in lettuce Lettuce TAG-specific contig information 14 18 0 278 69 336 0 11 30 78 85 60 29 738 140 0 100 200 300 400 500 600 700 800 TAG0(cls) TAG1(rot) TAG2(no) TAG3(flr) TAG4(flo) TAG5(chi) TAG6(nos) TAG7(rts) TAG8(shs) TAG9(gsd) TAG10(fls) TAG11(lvd) TAG_1_7(root) TAG_3_4_10(flower) TAG_7_8_10(stress) Tissue and Treatment contigs with coding region found in both genotypes Slide19:  Result – Rates of sequence divergence among tissue-specific contigs in sunflower and lettuce Slide20:  Result – Comparison of rates of sequence divergence for genes expressed in seeds versus other 0.00% 2.00% 4.00% 6.00% 8.00% 10.00% 12.00% 14.00% 16.00% DknHls Non-DknHls Seeds Content indel rate Substitution rate T-test: SubRateKH vs SubRateNonKH P-value = 0.0009414 Other Slide21:  Result – Rates of sequence divergence among treatment-specific contigs in sunflower and lettuce Slide22:  Conclusion2 As predicted, sunflower genes expressed in seeds evolve significantly faster than genes expressed in other tissues. Artificial selection for large seeds and high seed oil content may contribute to these higher rates. For lettuce, there are no significant differences in rates of sequence evolution among different tissues No differences were found in sunflower or lettuce among biotic and abiotic stress treatments Goals:  Goals Compare distribution of indels and base substitutions among closely related lettuce and sunflower EST sequences Compare rates of EST sequence divergence for genes from different tissue types and metabolic pathways Compare rates of EST sequence divergence from different pathway, and protein evolution among specific genes along major metabolic pathways Data Analysis – EST divergence among metabolic pathways:  Data Analysis – EST divergence among metabolic pathways To identify contigs for specific pathways, the metabolic pathway information from TAIR (The Arabidopsis Information Resource: http://www.arabidopsis.org/) database was utilized. Each contig in the CGPDB was assigned to an Arabidopsis gene locus (or remained unassigned) based on the BLAST results. Genes (contigs) for different metabolic pathways were clustered and protein divergence was estimated. Data Analysis – protein evolution along major metabolic pathways:  Data Analysis – protein evolution along major metabolic pathways Metabolic pathways: Lipid metabolic pathways Phenylpropanoid biosynthetic pathways Cellulose, lignin, sucrose …etc. metabolic pathways The nonsynonymous substitution rate (Ka) was calculated for enzymes in different positions along pathways Software DnaSP 4.0 was utilized for this calculation Result – comparison of metabolic pathway genes between CGPDB and TAIR:  Result – comparison of metabolic pathway genes between CGPDB and TAIR Based on the blast results, the contigs in CGPDB were compared with genes in TAIR and assigned to appropriate pathways Currently there are 186 pathways with more than 800 unique reactions in the TAIR database. For these reactions, 1144 unique locus_iDs were assigned to the enzymes involved. Among the TAIR loci, 72.1% match Contigs in the sunflower database and 83.15% match Contigs in the lettuce database. Result – Rates of sequence evolution for sunflower metabolic pathway-specific contigs:  Result – Rates of sequence evolution for sunflower metabolic pathway-specific contigs Result – Rates of sequence evolution for lettuce metabolic pathway-specific contigs:  Result – Rates of sequence evolution for lettuce metabolic pathway-specific contigs Result – Nonsynonymous substitution rate (Ka) for genes along four metabolic pathways in sunflower and lettuce:  Result – Nonsynonymous substitution rate (Ka) for genes along four metabolic pathways in sunflower and lettuce Conclusion3:  Conclusion3 Rates of sequence divergence did not differ among metabolic pathways Rates of protein evolution (Ka) did not vary along metabolic pathways (i.e., upstream genes evolved at the same rate as downstream genes) Summary:  Summary Substitutions are much more frequent than indels in both sunflower and lettuce Sunflower genes expressed in seeds evolve significantly faster than genes expressed in other tissues There are no significant differences in rates of sequence evolution among different tissues in lettuce Rates of sequence divergence did not vary significantly either among or along metabolic pathways in either sunflower or lettuce Acknowledge:  Acknowledge Thanks Dr. Loren Rieseberg Dr. Sun Kim Dr. Sheri Church Dr. Zhao Lai

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