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“Recent next generation sequencing results” MACHADO LAB.

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Presentation on theme: "“Recent next generation sequencing results” MACHADO LAB."— Presentation transcript:

1 “Recent next generation sequencing results” MACHADO LAB

2 SPRING 2013

3 …….

4 Phylogeny reconstruction

5 Population Genetics

6 My Sequence output: Graduate Student~440 Kb Postdoc~850 Kb Now… Rice project~430 Gb

7 My Sequence output: Graduate Student~440 Kb Postdoc~850 Kb Now…using NGS.. Rice project~430 Gb (Only 41 “experiments”)

8 Methods to study the Transcriptome Variety of methods, Illumina is the most common DNA RNA DNA RNA

9 Next Generation Sequence is also used to study gene expression The short fragments are mapped to the genome Number of mapped reads correlated with expression level RNA-Seq

10 Phylogeny of a human pathogen (32 genes) Carlos Flores-Lopez Sequencing >24 genomes from Trypanosoma cruzi to characterize history of gene exchange and identify genes under selection Uses of NGS: Phylogenomics

11 Uses of NGS: Mapping Find genomic regions underlying phenotypic differences NGS: sequence pools to identify candidate regions, or genotype using NGS-based methods (e.g. RAD tags)

12 psebog x pse x F1 x x Fertile Sterile Fertile D. pseudoobscura vs D. p. bogotana F1 Fertile Levi Teitz Uses of NGS: Mapping Sequencing pools of fertile and sterile 5 th generation backcrossed males to identify genomic regions associated with hybrid male sterility

13 1 st instar 24-32 h 1 st instar 24-32 h 3 rd instar 120-128 h 3 rd instar 120-128 h Pupa (yellow) 8-16 h after puparium formation Pupa (yellow) 8-16 h after puparium formation Adult 7 day old Adult 7 day old D. pseudoobscura (4) D. persimilis (3) H1 (♀pse x ♂per) D. pseudoobscura (4) D. persimilis (3) H1 (♀pse x ♂per) Uses of NGS: Studying the transcriptome Kevin Nyberg Kawther Abdilleh Patterns of sex-bias and expression divergence during development, expression and evolution of ncRNAs, evolution of coexpressed genes and networks

14 Uses of NGS: Understanding the history and genetic basis of domestication

15 O. glaberrima O. barthii African rice domestication 41 resequenced individuals (~30X)

16 Identification of candidate regions harboring adaptive genes associated with the domestication process Strong directional selection expected to cause selective sweeps in genomic regions associated with phenotypes under selection Artificial selection during domestication and crop improvement involves selection of specific alleles at genes controlling key morphological and agronomic traits, and result in reduced genetic diversity relative to unselected genes.

17 Chromosome Nucleotide diversity by chromosome (100 Kb windows) Π per 100Kb P < 0.001 Every chromosome

18 Chromosome Significant regions>200Kb >300Kb 12241 2142 360 4163 5121 6142 7152 880 9811 1040 1161 121741 Total142203 Regions with significantly low polymorphism ratios (“ROD”, 100 Kb windows). Empirical distribution used to determine significance (5% tail of distribution)

19 Uses of NGS: Making dreams come true.. Addressing questions in non-model organisms with no genomic resources

20 Under neutrality a positive correlation between levels of genetic polymorphism (heterozygosity) and population size is expected. Larger populations are expected to harbor more genetic variation H = 4N  /(1+ 4N  )

21 Weak correlation between population size and variation Modified from Nevo et al. (1984)

22 0 0.002 0.004 0.006 0.008 0.010 0.012 00.20.40.60.81 Proportion of single foundress broods (pollinating wasps, Pegoscapus sp.) Nucleotide diversity   Inbreeding  P = 0.0016  P = 0.0109 COI (mtDNA)

23 Nuclear marker: 1G04  p < 0.00001;  p < 0.00001  

24 Population structure can be quantified using: 1. Proportion of broods with different numbers of foundresses 2. Genetic data

25 Uses of NGS: Making dreams come true.. Collecting RNAseq data to characterize levels and patterns of genetic variation across multiple (5-10) species with different mating system (along a continuum of inbreeding levels) and across thousands of genes.

26 “Recent next generation sequencing results” MACHADO LAB


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