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Seminar In Ecology

by: Shaina Mohr PhD

Seminar In Ecology ECL 290

Shaina Mohr PhD
GPA 3.51


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Class Notes
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Popular in Ecology

This 12 page Class Notes was uploaded by Shaina Mohr PhD on Tuesday September 8, 2015. The Class Notes belongs to ECL 290 at University of California - Davis taught by Staff in Fall. Since its upload, it has received 85 views. For similar materials see /class/187702/ecl-290-university-of-california-davis in Ecology at University of California - Davis.


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Date Created: 09/08/15
Genetic Parentage Analysis Software Cervus 30 Table 1 The implications of various types of samples from natural populations for the reconstruction of parentage How many of the unknown parents can I sample Can I sample large groups of full or halfslbs How many parents of each offspring are known a priori Preferred technique What can I do if I don39t powerful have sufficiently markers for the preferred technique Possible computer programs see Table 2 All or some Yes or no Both Gmotype some individuals to Nothing No program necessary verity paren t ofispring relationships All Yes One Exclusion cormborated by Categorical alloca on fractional NEWPAAMOZ PARENTE PATR reconstruction of parental allocation estimate number of parents or KINSHIP for exclusion or allocation GERUD for genotypes from progeny arrays reconstruction All Yes Neither Complete exclusion It progeny Categorical allocation fractional PROBMAX PAPA FAMDZ or PARENTE for arrays contain halfsibs allocation estimate number of parents exclusion or allocation GERUD for reconstruction of parental reconstruction genotypes All No One Complete exclusion Categorical allocation fractional mawea Amoz PARENTE PATRI or KINSHE allocation kinship techniques for exclusion or allocation All No Neither Complete exclusion Categorical allocation fractional PROBMAX PAPA FAMOZ or PARENTE for allocation kinship techniques exclusion or alhcation Some Yes One Reconstruction of parental Categorical allocation fractional NEWPAAMOL PARENTE PAIR or RINSE genotypes Complete exclusion allocation estimate number of parents for exclusion or allocation GERUD for reconstructit or categorical fractional allocation Some Yr Neither Complete exclusion or Categorical allocation fractional N39EWPA AMDZ PARENTE KINSHIP categorieal fractional allocation allocation estimate number of parents PROBMAX or PAPA1 for exclusion or allocation Reconstruction of parental CERUD for reconstruction genotypes if progeny arrays contain halfsibs Some No One or neithm Complete exclusion or Kinship techniques N39EWPAAMOZ PARENTE PATRI if one categoricalfractional allocation parent is known KINSHIP PROBMAXI or PARU for exclusion or allocation None Yes One Reconstruction of parental Estimate number of parents GERUD for reconstruction genotypes None Yes Neither Reconstruction of parental Estimate number of parents GERUD for reconstruction genotypes if progeny arrays contain halfsins None No One or neither Use kinship or relatedness Nothing ICLNSHIP or RELATEDNESSZ tech niqu es 1Parentpair allocation techniques are particularly sensitive to incomplete sampling of candidate parents and should be used earm ully here 2RELATEDmsss is available from http gsoftsmuedu Jones et al 2003 Mol Eco122511 Table 2 Computer programs for reconstructing parentage in natural populations Available functions Ability to accommodate error N ull Genotyping Method Program I M1 PFl PRt ICd ECU Elquot Required info Type of genetic markers alleles error Mutation Comments Exclusion PRoaMmc X Genotypes of offspring Diploid codominant Good Moderate Moderate Can specify parental and sexed parean Diploid dominant mating combinations NEWPAT X X X Genotypes of offspring Di ploid codominant Moderate Moderate Moderate Can calculate and sexed parents Sexlinked loci con dence intervals for null allele frequency KJNSHIPl X X Genotypes of offspring Diploid codominant None None None C e aploids as and parents wall 391 39linl wir l Categorical allocation CERVUSY X X X X Genotypes of offspring Diploid codominant Moderate Good Good Excellent manual and and sexed parents user interface Calculates expected null quot PAPAk X X Genotypes of offspring Diploid codominant Poor Good Good Easy to use and and parents excellent interface FAMOZ X X X X X Genotypes of offspring Diploid dominant Poor Good Good Can estimate cryptic and parents Diploid codominant gene ow Cytoplasmic Difficult file format PARENTE39 X X X Genotypes of offspring Diploid codominant Poor Good Good Can take into account nd parents dates of birth and death Fractional allocation ATR X X Genotypes of parentoffspring Diploid codominant None None None Can test relative pairs and sexed parents reproductive success of different groups Can also be used for categorical allocation Parental reconstruction GrowlB X X X Genotypes of known Diploid codominant None None None Uses multilocus data to parent with a large group of its progeny e ermine the minimum number of sites for a amily Pa ternity maternity see lnformati on box 5 39 cation see Information box Parental reconstruction see information box dAbility to assign statistical confidence for particular parentioffspring pairs CAbility r con dence 39 39 IAbility to calculate exclusion probabilitia sDanzmannl quot 39 r I hWorthington Wilmer ei al I http IGoodnight S Queller 1999 available at http gsoftsmuedu l a Marshall a al 1998 available at http heliosbtoedacluk evolgen cervus cervuslhtml Ln L v n basis PROEMAX um panhtml IL u r hi lll tv il t r lGerberHal 39 quot hnp 39 inra D quot an t u r Cercueil rt 1 wwa bl htn Signorovitch amp Nielsen 2002 available at http WWWbiomcornelleduilomepagesR H L L s r t v t t r 1l asmusiNielsen t39i leshtml Jones et al 2003 Mol ECOI122511 Cervus 30 Likelihood based parentage assignment MaternityPaternity Parent Pair Assignment Have to have at least some parents genotypes Likelihood equations from Marshall et a1 1998 Revised by Kalinowski et a1 2007 0 New version accounts for problems in Marshall s method of calculating genotyping error it in ated the rate in which errors were expected to be observed it did not exclude parents when it should have AssumptionsLimitations Genotyping errors are independent and constant across loci No linkage HardyWeinberg Equilibrium Can handle minor deviations at a few loci Codominant diploid data Analyses Steps 1 Allele Frequency Analysis 2 Simulation 3 Parentage Analysis Allele Freq Analysis Output Allele Frequency Analysis On Screen Output Locus k N HObs HEXp PIC NE1P NE2P NEPP NEI NESI HW FNull A 8 135 063 059 055 07939 062 042 019 050 NS 0050 B 17 135 089 087 086 040 024 009 002 032 NS 0012 C 9 134 079 084 0 048 031 014 004 034 NS 0027 NE Nonexculsion probability probability of not excluding a single unrelated candidate parent parent that is NOT the real parent is included as a potential parent NElP NE prob for a single parent NE2P NE prob for a single parent when one parent is known NEPP NE prob for a parent pair probability a NE prob is not used for likelihood calculations but may be useful for comparisons to other data or choosing loci Simulations Purpose Estimate the resolving power of loci given their allele frequencies Estimate critical values of LCD or Delta allowing to statistically analyze the con dence of assignment Generate pair of parent genotypes and several unrelated parent genotypes using allele frequencies Creates series of progeny from the parent pair Calculates likelihood of each true parent and the unrelated parents for each offspring Simulations cont Scores from the simluated data are used to determine the critical LCD or Delta score for the real parentage analysis Simluation options Selffertilization InbreedingRelated parents Parentage Analysis Types of analyses One parent is known paternitymaternity Neither parent is known but have potential parent genotypes Sexes unknown Sexes known Parentage Output Loci Candidate Loci Pair loci Pair loci Pair LOD Pair Offspring ID typed mother ID typed compared mismatching score Pair Delta confidence Deer5 29 Deer25 29 29 9 289EO1 000EOO Deer34 29 Deer119 29 29 O 230E01 230E01 Deer35 29 Deer21 29 29 1 947E00 947E00 Candidate 39 Pair loci Pair loci Pair LOD Pair Offspring ID father ID compared mismatching score Pair Delta confidence Deer5 Deer65 635E00 000EOO Deer34 Deer31 991E00 000EOO Deer35 Deer87 571E00 571E00 Trio loci Trio loci Trio LOD Trio Offspring lD compared mismatching score Trio Delta confidence Deer5 29 11 237E01 000E00 Deer34 29 11 456E00 000E00 Deer35 29 4 205E01 985E00 Things to Consider Guessing at the proportion of parents sampled Linkage Dealing With Null Alleles Run it several times with various options


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