Skip to main content
SpringerLink
Log in

Statistical Advances in Functional Genomics

  • Chapter
Genomics-Assisted Crop Improvement

Abstract

Statistics, agriculture, and genetics share a long successful pre-genomic history that is based on solid principles of experimental design and analysis of variation. In the era of ‘omics it is essential that statistical and mathematical standards, as well as guidelines for the experimental design and analysis of biological studies are upheld. The main message of this chapter recalls past statistical issues, discusses current statistical advances that pertain to understanding complex traits, and promotes ideas about both the data and statistical genomic models of the future.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Basten C, Weir BS, Zeng Z-B (1995–2004) QTL cartographer. Department of statistics, North carolina State University, Raleigh, NC

    Google Scholar 

  • Bayes T (1763) An essay towards solving a problem in the doctrine of chances. Philos T Roy Soc 53:370–418

    Article  Google Scholar 

  • Berger JO (1985) Statistcial decision theory and bayesian analysis. 2nd edn. Springer-Verlag, New York

    Google Scholar 

  • Berlin JA, Colditz GA (1999) The role of meta-analysis in the regulatory process for foods, drugs, and devices. J Am Med Assoc 281:830–834

    Article  CAS  Google Scholar 

  • Bogdan M, Ghosh JK, Doerge RW (2004) Modifying the schwarz bayesian information criterion to locate multiple interacting quantitative trait loci. Genetics 167:989–999.

    Article  PubMed  CAS  Google Scholar 

  • Borevitz JO, Liang D, Plouffe D, Chang H-S, Zhu T, Weigel D, Berry CC, Winzeler E, Chory J (2003) Large-scale identification of single-feature polymorphisms in complex genomes. Genome Res 13: 513–523

    Article  PubMed  CAS  Google Scholar 

  • Brem RB, Kruglyak L (2005) The landscape of genetic complexity across 5,700 gene expression traits in yeast. Proc Nat Acad Sci USA 102:1572–1577

    Article  PubMed  CAS  Google Scholar 

  • Broman KW, Speed TP (2002) A model selection approach for the identification of quantitative trait loci in experimental crosses. JR Stat Soc B 64:641–656

    Article  Google Scholar 

  • Carlborg Ö (2002) New methods for mapping quantitative trait loci. PhD Thesis, Acta Universitatis Agriculturae Sueciae. Veterinaria 121. Swedish University of Agricultural Sciences, Uppsala, Sweden

    Google Scholar 

  • Carlborg Ö, Andersson L, Kinghorn B (2000) The use of a genetic algorithm for simultaneous mapping of multiple interacting quantitative trait loci. Genetics 155:2003–2010

    PubMed  CAS  Google Scholar 

  • Carlborg Ö, Andersson-Eklund L, Andersson L (2001) Parallel computing in interval mapping of quantitative trait loci. J Hered 92:449–451

    Article  PubMed  CAS  Google Scholar 

  • Carlborg Ö, De Koning DJ, Manly KF, Chesler E, Williams RW, Haley CS (2005) Methodological aspects of the genetic dissection of gene expression. 21: 2383–2393

    CAS  Google Scholar 

  • Doerge RW (2002) Mapping and analysis of quantitative trait loci in experimental populations. Nat Rev Genet 3:43–52

    Article  PubMed  CAS  Google Scholar 

  • Doerge RW, Zeng Z-B, Weir BS (1997) Statistical issues in the search for genes affecting quantitative traits in experimental populations. Stat Sci 12:195–219

    Article  Google Scholar 

  • Efron B (1986) What Isn’t everyone a bayesian. Am Stat 401:1–5

    Article  Google Scholar 

  • Glass GV (1976) Primary, secondary, and meta-analysis of research. Educ Res 5(10):3–8

    Google Scholar 

  • Hazen SP, Kay SA (2003) Gene arrays are not just for measuring gene expression. Trends Plant Sci 8: 413–416

    Article  PubMed  CAS  Google Scholar 

  • Jansen RC (1993) Interval mapping of multiple quantitative trait loci. Genetics 135:205–211

    PubMed  CAS  Google Scholar 

  • Jansen RC, Nap JP (2001) Genetical genomics: the added value from segregation. Trends Genet 17:388–391

    Article  PubMed  CAS  Google Scholar 

  • Jansen RC, Stam P (1994) High resolution of quantitative traits into multiple loci via interval mapping. Genetics 136:1447–1455

    PubMed  CAS  Google Scholar 

  • Jin W, Riley RM, Wolfinger RD, White KP, Passador-Gurgel G, Gibson G (2001) The contributions of sex, genotype and age to transcriptional variance in drosophila melanogaster. Nat Genet 29:389–395

    Article  PubMed  CAS  Google Scholar 

  • Jorgensen R (2006) Large-scale biology. Plant Cell 18: 2095–2096

    Article  CAS  Google Scholar 

  • Kao CH, Zeng Z-B, Teasdale RD (1999) Multiple interval mapping for quantitative trait loci. Genetics 152:1203–1216

    PubMed  CAS  Google Scholar 

  • Kaski S, Nikkila J, Sinkkonen J, Lathi L, Knuttila JEA, Roos C (2005) Associative clustering for exploring dependencies between functional genomic data sets. IEEE/ACM T Comput Bi 2:203–216

    Article  CAS  Google Scholar 

  • Kassirer JP (1992) Clinical trials and meta-analysis. What do they do for us? New Engl J Med 327–332

    Google Scholar 

  • Kendziorski C, Wang P (2006) A review of statistical methods for expression quantitative trait loci mapping. Mamm Genome 17:509–517.

    Article  PubMed  Google Scholar 

  • Kim, K (2007) Statistical issues in mapping genetic determinants of expression level polymorphisms. PhD Dissertation. Department of Statistics, Purdue University. West Lafayette, IN USA

    Google Scholar 

  • Kim K, West MAL, Michelmore RW, Clair DAS, Doerge RW (2005) Old methods for new ideas: genetic dissection of the determinants of gene expression levels. In: Gustafson JP, Shoemaker R, Snape JW (eds) Genome exploitation: data mining the genome. The 23rd volume in the stadler symposia. Springer, New York, pp 89–105

    Google Scholar 

  • Kliebenstein DJ, West MAL, van Leeuwen H, Loudet O, Doerge RW, St. Clair DA (2006) Identification of QTLs controlling gene expression networks defined a priori. BMC Bioinformatics 7:308

    Article  PubMed  CAS  Google Scholar 

  • Kliebenstein DJ, West MAL, van Leeuwen H, Kim K, Doerge, RW, Michelmore RW, St. Clair DA (2006) Genomic survey of gene expression diversity in Arabidopsis thaliana. Genetics 172:1179–1189

    Article  PubMed  Google Scholar 

  • Lander ES Botstein D (1989) Mapping mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics 121:185–199 (1989); erratum (1994) 136:705

    Google Scholar 

  • Liang Y, Kelemen A (2006) Associating phenotypes with molecular events: recent statistical advances and challenges underpinning microarray experiments. Funct Integr Genomics 6:1–13

    Article  PubMed  CAS  Google Scholar 

  • Lippman Z, Gendrel A-V, Black M, Vaughn M, Dedhia N, McCombie WR, Lavine K, Mittal V, May B, Kasschau K, Carrington JC, Doerge RW, Colot V, Martienssen R (2004) Transposable elements mediate heterochromatin and epigenetic control. Nature 430:471–476

    Article  PubMed  CAS  Google Scholar 

  • Martienssen RA, Doerge RW, Colot V (2005) Epigenomic mapping in Arabidopsis using tiling microarrays. Chromosome Res 13:299–308

    Article  PubMed  CAS  Google Scholar 

  • Miescher F (1871) Ueber die chemische Zusammensetzung der Eiterzellen. Med Chem Unt 4:441–460

    Google Scholar 

  • Nakamighi R, Ukai Y, Kishino H (2001) Detection of closely linked multiple quantitative trait loci using genetic algorithm. Genetics 158:465–475

    Google Scholar 

  • Nettleton D (2006) A discussion of statistical methods for design and analysis of microarray experiments for plant scientists. Plant Cell 18:2112–2121

    Article  PubMed  CAS  Google Scholar 

  • Petronis A (2006) Epigenetics and twins: three variations on the theme. Trends Genet 22:347–350

    Article  PubMed  CAS  Google Scholar 

  • Potokina E, Caspers M, Pradad M, Kota R, Zhang H, Sreenivasulu N, Wang M, Graner A (2004) Functional association between malting quality trait components and cDNA array based expression patterns in barley (Hordeum vulgare L.). Mol Breeding 14:153–170

    Article  CAS  Google Scholar 

  • Qiu J (2006) Unfinished symphony. Nature 441:143–145

    Article  PubMed  CAS  Google Scholar 

  • Richards, EJ (2006) Inherited epigenetic variation – revisiting soft inheritance. Nat Genet Rev 7:395–401

    Article  CAS  Google Scholar 

  • Rusakov D, Geiger D (2005) Asymptotic model selection for naive bayesian networks. J Mach Learn Res 6:1–35

    Google Scholar 

  • Sax K (1923) The association of size differences with seed-coat pattern and pigmentation in Phaseolus vulgaris. Genetics 8:552–560

    PubMed  CAS  Google Scholar 

  • Schadt EE, Monks SA, Drake TA, Lusis AJ, Che N, Collnayo V, Ruff TG, Milligan SB, Lamb JR, Cavet G, Linsley PS, Mao M, Stoughton RB, Friend SH (2003) Genetics of gene expression surveyed in maize, mouse, and man. Nature 422:297–302

    Article  PubMed  CAS  Google Scholar 

  • Schadt EE, Lamb J, Yang X, Zhu J, Edwards S, GuhaThakurta D, Sieberts SK, Monks S, Reitman M, Zhang C, Lum PY, Leonardson A, Thieringer R, Metzger JM, Yang L, Castle J, Zhu H, Kash SF, Drake TA, Sachs A, Lusis AJ (2005) An integrative genomics approach to infer causal associations between gene expression and disease. Nat Genet 37:710–717

    Article  PubMed  CAS  Google Scholar 

  • Searle S (1971) Linear models. John Wiley & Sons, New York

    Google Scholar 

  • Segal E, Pe’er D, Regev A, Koler D, Friedman N (2005) Learning module networks. J Mach Learn Res 6:557–588

    Google Scholar 

  • Segerstrom SC, Miller GE (2004) Psychological stress and the human immune system: a meta-analytic study of 30 years of inquiry. Psychol Bull 130:601–630

    Article  PubMed  Google Scholar 

  • Singer T, Fan Y., Chang H-SC, Zhu T, Hazen SP, Briggs SP (2006) A high-resolution map of Arabidopsis recombinant inbred lines by whole-genome exon array hybridization. PLoS Genet 2:1–10

    Article  CAS  Google Scholar 

  • Steinmetz LM, Davis RW (2004) Maximizing the potential of functional genomics. Nat Genet Rev 5:190–201

    Article  CAS  Google Scholar 

  • Steinmetz LM, Sinha H, Richards DR, Spiegelman JI, Oefner PJ, Mc-Cusker JH, Davis RW (2002) Dissecting the architecture of a quantitative trait locus in yeast. Nature 416:326–330

    Article  PubMed  CAS  Google Scholar 

  • Stevens JR (2005) Meta-analytic approaches for microarray data. PhD dissertation. Department of Statistics, Purdue University, West Lafayette, IN USA

    Google Scholar 

  • Stevens JR, Doerge RW (2005a) Combining affymetrix microarray results. BMC Bioinformat 6:57

    Article  CAS  Google Scholar 

  • Stevens J, Doerge RW (2005b) Meta-analysis combines affymetrix microarray results across laboratories. Compar Funct Genom 6:116–122

    Article  CAS  Google Scholar 

  • Tanksley SD (1993) Mapping polygenes. Annu Rev Genet 27:205–233

    Article  PubMed  CAS  Google Scholar 

  • Thoday JM (1961) Location of polygenes. Nature191:368–370

    Article  Google Scholar 

  • Trifonov EN (2000) Earliest pages of bioinformatics. Bioinformatics 16:5–9

    Article  PubMed  CAS  Google Scholar 

  • Waddington C (1942) The epigenotype. Endeavor 1: 18–20

    Google Scholar 

  • Wang D, Weaver ND, Kesarwani M, Dong X (2005) Induction of protein secretory pathway is required for systemic acquired resistance. Science 308:1036–1040

    Article  PubMed  CAS  Google Scholar 

  • Watson JD, Crick FHC (1953) Molecular structure of nucleic acids. A structure for deoxyribose nucleic acid. Nature 171:737–738

    Article  PubMed  CAS  Google Scholar 

  • Wayne ML, McIntyre LM (2002) Combining mapping and arraying: an approach to candidate gene identi_cation. Proc Nat Acad Sci USA 99:14903–14906

    Article  PubMed  CAS  Google Scholar 

  • West MAL, van Leeuwen H, Kozik A, Kliebenstein DJ, Doerge RW, St. Clair DA, Michelmore RW (2006) High-density haplotyping with microarray-based expression and single feature polymorphism markers in Arabidopsis. Genome Res 16:787–795

    Google Scholar 

  • Winzeler EA, Richards DR, Conway AR, Goldstein AL, Kalman S, McCullough MJ, McCusker JH, Stevens DA, Wodicka L, Lockhart DJ et al (1998) Direct allelic variation scanning of the yeast genome. Science 281:1194–1197

    Article  PubMed  CAS  Google Scholar 

  • Wu R, Lin M (2006) Functional mapping – how to map and study the genetic architecture of dynamic complex traits. Nat Genet Rev 7:229–237

    Article  CAS  Google Scholar 

  • Yvert G, Brem RB, Whittle J, Akey JM, Foss E, Smith EN, Mackelprang R, Kruglyak L (2003) Trans-acting regulatory variation in Saccharomyces cerevisiae and the role of transcription factors. Nat Genet 35:57–64

    Article  PubMed  CAS  Google Scholar 

  • Zeng Z-B (1993) Theoretical basis of precision mapping of quantitative trait loci. Proc Natl Acad Sci USA 90:10972–10976

    Article  PubMed  CAS  Google Scholar 

  • Zeng Z-B (1994) Precision mapping of quantitative trait loci. Genetics 136:1457–1468

    PubMed  CAS  Google Scholar 

  • Zhang H, Yazaki J, Sundaresan A, Cokus S, Chan S, Chen H, Henderson IR, Shinn P, Pellegrini M, Jacobsen SE, Ecker JR (2006) Genome-wide high-resolution mapping and functional analysis of DNA methylation in Arabidopsis. Cell (Resource) 126:1–13

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Departments of Statistics and Agronomy, Purdue University, 150 North University Street, West Lafayette, IN 47907, USA

    Rebecca W. Doerge

Authors
  1. Rebecca W. Doerge
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. ICRISAT, Patancheru, India

    Rajeev K. Varshney

  2. University of Bologna, Italy

    Roberto Tuberosa

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer

About this chapter

Cite this chapter

Doerge, R.W. (2007). Statistical Advances in Functional Genomics. In: Varshney, R.K., Tuberosa, R. (eds) Genomics-Assisted Crop Improvement. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-6295-7_14

Download citation

Publish with us

Policies and ethics

Search

Navigation