Dataset Information

Family-Based Multi-SNP X Chromosome Analysis Using Parent Information.

ABSTRACT: We propose a method for association analysis of haplotypes on the X chromosome that offers both improved power and robustness to population stratification in studies of affected offspring and their parents if all three have been genotyped. The method makes use of assumed parental haplotype exchangeability (PHE), a weaker assumption than Hardy-Weinberg equilibrium (HWE). PHE requires that in the source population, of the three X chromosome haplotypes carried by the two parents, each is equally likely to be carried by the father. We propose a pseudo-sibling approach that exploits that exchangeability assumption. Our method extends the single-SNP PIX-LRT method to multiple SNPs in a high linkage block. We describe methods for testing the PHE assumption and also for determining how apparent violations can be distinguished from true fetal effects or maternally-mediated effects. We show results of simulations that demonstrate nominal type I error rate and good power. The methods are then applied to dbGaP data on the birth defect oral cleft, using both Asian and Caucasian families with cleft.

SUBMITTER: Wise AS

PROVIDER: S-EPMC4761843 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Publications

Family-Based Multi-SNP X Chromosome Analysis Using Parent Information.

Wise Alison S AS Shi Min M Weinberg Clarice R CR

Frontiers in genetics 20160222

We propose a method for association analysis of haplotypes on the X chromosome that offers both improved power and robustness to population stratification in studies of affected offspring and their parents if all three have been genotyped. The method makes use of assumed parental haplotype exchangeability (PHE), a weaker assumption than Hardy-Weinberg equilibrium (HWE). PHE requires that in the source population, of the three X chromosome haplotypes carried by the two parents, each is equally li ...[more]

PMID: 26941777

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Project description:BackgroundWith an increasing world population and a gradual decline in the amount of arable land, food security remains a global challenge. Continued increases in rice yield will be required to break through the barriers to grain output. In order to transition from hybrid rice to super-hybrid rice, breeding demands cannot be addressed through traditional heterosis. Therefore, it is necessary to incorporate high yield loci from other rice genetic groups and to scientifically utilize intersubspecific heterosis in breeding lines. In this study, 781 lines from a segregating F2 population constructed by crossing the indica variety, "Giant Spike Rice" R1128 as trait donor with the japonica cultivar 'Nipponbare', were re-sequenced using high-throughout multiplexed shotgun genotyping (MSG) technology. In combination with high-density single nucleotide polymorphisms, quantitative trait locus (QTL) mapping and genetic effect analysis were performed for five yield factors (spikelet number per panicle, primary branches per panicle, secondary branches per panicle, plant height, and panicle length) to explore the genetic mechanisms underlying the formation of the giant panicle of R1128. Also, they were preformed to locate new high-yielding rice genetic intervals, providing data for super-high-yielding rice breeding.ResultsQTL mapping and genetic effect analysis for five yield factors in the population gave the following results: 49 QTLs for the five yield factors were distributed on 11 of 12 chromosomes. The super-hybrid line R1128 carries multiple major genes for good traits, including Sd1 for plant height, Hd1 and Ehd1 for heading date, Gn1a for spikelet number and IPA1 for ideal plant shape. These genes accounted for 44.3%, 21.9%, 6.2%, 12.9% and 10.6% of the phenotypic variation in the individual traits. Six novel QTLs, qph1-2, qph9-1, qpl12-1, qgn3-1, qgn11-1and qsbn11-1 are reported here for the first time.ConclusionsHigh-throughout sequencing technology makes it convenient to study rice genomics and makes the QTL/gene mapping direct, efficient, and more reliable. The genetic regions discovered in this study will be valuable for breeding in rice varieties because of the diverse genetic backgrounds of the rice.

Dataset Information

Family-Based Multi-SNP X Chromosome Analysis Using Parent Information.

Publications

Family-Based Multi-SNP X Chromosome Analysis Using Parent Information.

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