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Биоинформатика сложных количественных признаков Цель: Создание методической базы для выяснения генетической природы сложных признаков. Задачи: Разработка новых моделей контроля сложных признаков, новых методов картирования и идентификации контролирующих их генов и использование этих разработок для получения новых знаний о генетической архитектуре сложных признаков человека. Этап I: Параметрический анализ сцепления по родословным неограниченно большого размера (алгоритм и пакет программ)

Биоинформатика сложных количественных признаков

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Биоинформатика сложных количественных признаков Цель: Создание методической базы для выяснения генетической природы сложных признаков. - PowerPoint PPT Presentation

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  • : . : , . I: ( )

  • Peltonen et al. Science, 2001 291:5507, 1224-1229

  • EUROSPAN (European Special Population Network) project 1. Counties of Norrbotten and Vsterbotten, Swedish 2. Archipelago of Orkney, Scottish3. South-western area of the Netherlands4. Venosta Valley, South Tyrol, Italy 5. villages of Vis and Komiza, Dalmatian island, CroatiaJohansson et al. Hum Mol Biol, 2009 18: 373-380

  • Erasmus Rucphen Family (ERF) studyAulchenko et al, 2007

  • :LINKAGE (ftp://linkage.rockefeller.edu/software/linkage) FASTLINK (http://www.ncbi.nlm.nih.gov/CBBresearch/Schaffer/fastlink.html)vitesse (http://watson.hgen.pitt.edu/docs/vitesse.html)GENEHUNTER-MODSCORE (http://www.staff.uni-marburg.de/~strauchk/software.html) SAGE (http://darwin.cwru.edu/sage/) SIMWALK2 (http://watson.hgen.pitt.edu/register/)

  • i pedigree ancestors,j offspring,k observed individuals i ,j ,k

    NRunning time |G|=10108 sec111.5 min1214 min13138 min15about 10 days

  • Lander-GreenElston-Stewart ( 30 ), ,

  • : -2143214321321

  • ( ) -

  • :1. (Stricker, C., Fernando, R.L. & Elston, R.C. (1996) An algorithm to approximate the likelihood for pedigree data with loops by cutting. Theor Appl Genet, 91, 1054-63)

    2. (Axenovich, T.I., Zorkoltseva, I.V., Liu, F., Kirichenko, A.V. & Aulchenko, Y.S. (2008) Breaking loops in large complex pedigrees. Hum Hered, 65, 57-65)LH0 = LH1/LH(k)kk

  • :1.

    2. (Belonogova, N.M. & Axenovich, T.I. (2007) Optimal peeling order for pedigrees with incomplete genotypic information. Comput Biol Chem, 31, 173-7)

    3. (O'Connell, J.R. & Weeks, D.E. (1999) An optimal algorithm for automatic genotype elimination. Am J Hum Genet, 65(6), 1733-40)

  • - - ~|N||G|

    117621990 624529 321 0.008 sec6 sec

  • Peeling NP on a parentPeeling NP on one of the offspringRunning time

  • Pedigree(N)MaximumMeanS.E.Minimum(optimal)Ratio mean/optimalHuman(114)6.76 x 1046.56 0.09 x 1043.05 x 1042.15Silver fox(1845)1.34 x 1071.31 0.001 x 1074.13 x 1063.18Polar fox(952)2.66 x 1078.28 0.23 x 1064.60 x 1061.80

  • : 0 zi1, Z0 NNZi=0.5Zi=0.75Zi=0.9: F>1 yi=Fzi,

    Z=yi/FN

    lnZ=ln(yi)-NlnF.

  • Lets define the factor

    where P(Xi(s)|gi) is the result of peeling s on individual i.

    Lets introduce r(Xi(s)|gi)= P(Xi(s)|gi)/F(s) so that r(Xi(s)|gi)= 1. Then

  • ( double precision)

    117621990 5516666 6391719LH10-83910-1912ln LH- 1932.6- 4402.3

  • : x = g + G + eg [g: QQ, Qq qq]G [N(0,2G)]e [N(0,2e)]

  • (Fernando, R.L., Stricker, C. & Elston, R.C. (1994) The finite polygenic mixed model: an alternative formulation for the mixed model of inheritance. Theor Appl Genet, 88, 573-80)n ( 0 1), k (G = dk) (Lange, K. (1997) An approximate model of polygenic inheritance. Genetics, 147, 1423-30)Ckk1+k2 C2n-k4n-k1-k2/ C2n4n, k1 k2

  • :p Q,QQ, Qq, qq , ,2e

    :21 = 3() 7()

    :n = 10 ,n = 55

  • MQscore_SNP1. :

    a) [recode_ped_2006.pl (http://mga.bionet.nsc.ru/soft/index.html)]

    b) [ pedpeel_2006_4.pl(http://mga.bionet.nsc.ru/soft/index.html)]

    )

  • MQscore_SNP

    2. [MQscore_SNP (http://mga.bionet.nsc.ru/soft/)]:

    a) MQscore_2point ,

    b) MQscore_2point_max ,

    ) MQscore_3point

  • MQscore_SNP

    3. : 5822, 2480, 5250, Pentium D 3a) MQscore_2point ,0.31 1 , 27 ,b) MQscore_2point_max ,8.28 1 , 30 ) MQscore_3point 14.25 , 52

  • MQscore_SNP4. :

    1. ( )

    2. ( LOD score > 1.5)

    3. LOD score > 1.5 ( LOD score)

    4. LOD score > 1.5(QTL )

  • The locus 16q24 showing the strongest linkage signal between markers rs299956 and rs2076962 was not mapped earlier as region contributing to normal variation of human height.

    We studied association in regions 80 90 Mb on chromosome 16 around significant linkage peak using additional 11840 SNPs. Nineteen markers in this region demonstrated FDR q-values less than 0.05. Seventeen of them were located between 81,882 and 81,967 kbp. This signal is located within the CDH13 (cadherin 13) gene (81,218,079 - 82,387,702 bp).

    For one of SNPs, rs1035569, having minimal p-value = 4.3x10-5 and q-value = 0.026, we estimated genotyping means. Mean height for AA, AG and GG genotypes of this marker was estimated as 175.14, 176.58 and 178.45 cm. The proportion of the total trait variance explained by genotypes of rs1035569 was estimated as 0.015.

    Lod ScoreCOL9A2NRXN14.04.02.0CDH13Chr 1Chr 2Chr 16