Medical Genetics Commons^™

Genetic Candidate Variants In Two Multigenerational Families With Childhood Apraxia Of Speech, Peter Beate, Ellen M. Wijsman, Alejandro Q. Nato Jr., University Of Washington Center For Mendelian Genomics, Mark M. Matsushita, Kathy L. Chapman, Ian B. Stanaway, John Wolff, Kaori Oda, Virginia B. Gabo, Wendy H. Raskind

Biochemistry and Microbiology

Childhood apraxia of speech (CAS) is a severe and socially debilitating form of speech sound disorder with suspected genetic involvement, but the genetic etiology is not yet well understood. Very few known or putative causal genes have been identified to date, e.g., FOXP2 and BCL11A. Building a knowledge base of the genetic etiology of CAS will make it possible to identify infants at genetic risk and motivate the development of effective very early intervention programs. We investigated the genetic etiology of CAS in two large multigenerational families with familial CAS. Complementary genomic methods included Markov chain Monte Carlo linkage …

Estimating Relationships Between Phenotypes And Subjects Drawn From Admixed Families., Elizabeth M. Blue, Lisa A. Brown, Matthew P. Conomos, Jennifer L. Kirk, Alejandro Q. Nato Jr., Alice B. Popejoy, Jesse Raffa, John Ranola, Ellen M. Wijsman, Timothy Thornton

Biochemistry and Microbiology

Background: Estimating relationships among subjects in a sample, within family structures or caused by population substructure, is complicated in admixed populations. Inaccurate allele frequencies can bias both kinship estimates and tests for association between subjects and a phenotype. We analyzed the simulated and real family data from Genetic Analysis Workshop 19, and were aware of the simulation model.

Results: We found that kinship estimation is more accurate when marker data include common variants whose frequencies are less variable across populations. Estimates of heritability and association vary with age for longitudinally measured traits. Accounting for local ancestry identified different true associations …

Mapping Genes With Longitudinal Phenotypes Via Bayesian Posterior Probabilities, Anthony Musolf, Alejandro Q. Nato Jr., Douglas Londono, Lisheng Zhou, Tara C. Matise, Derek Gordon

Biochemistry and Microbiology

Most association studies focus on disease risk, with less attention paid to disease progression or severity. These phenotypes require longitudinal data. This paper presents a new method for analyzing longitudinal data to map genes in both population-based and family-based studies. Using simulated systolic blood pressure measurements obtained from Genetic Analysis Workshop 18, we cluster the phenotype data into trajectory subgroups. We then use the Bayesian posterior probability of being in the high subgroup as a quantitative trait in an association analysis with genotype data. This method maintains high power (>80%) in locating genes known to affect the simulated phenotype …

Draft Genome Sequence For Pseudomonas Aeruginosa Strain Pao579, A Mucoid Derivative Of Pao381, T. Ryan Withers, Shannon L. Johnson, Hongwei D. Yu

Biochemistry and Microbiology

Pseudomonas aeruginosa is an opportunistic pathogen that establishes a chronic lung infection in individuals afflicted with cystic fibrosis. Here, we announce the draft genome of P. aeruginosa strain PAO579, an alginate-overproducing derivative of strain PAO381.

Global Analysis Of Gene Expression Changes During Retinoic Acid-Induced Growth Arrest And Differentiation Of Melanoma: Comparison To Differentially Expressed Genes In Melanocytes Vs Melanoma, Mary H. Estler, Goran Boskovic, James Denvir, Sarah Miles, Donald A. Primerano, Richard M. Niles

Biochemistry and Microbiology

BACKGROUND: The incidence of malignant melanoma has significantly increased over the last decade. Some of these malignancies are susceptible to the growth inhibitory and pro-differentiating effects of all-trans-retinoic acid (RA). The molecular changes responsible for the biological activity of RA in melanoma are not well understood.

RESULTS: In an analysis of sequential global gene expression changes during a 4-48 h RA treatment of B16 mouse melanoma cells, we found that RA increased the expression of 757 genes and decreased the expression of 737 genes. We also compared the gene expression profile (no RA treatment) between non-malignant melan-a mouse melanocytes and …