Dataset Information

Genotype calling in tetraploid species from bi-allelic marker data using mixture models.

ABSTRACT:

Background

Automated genotype calling in tetraploid species was until recently not possible, which hampered genetic analysis. Modern genotyping assays often produce two signals, one for each allele of a bi-allelic marker. While ample software is available to obtain genotypes (homozygous for either allele, or heterozygous) for diploid species from these signals, such software is not available for tetraploid species which may be scored as five alternative genotypes (aaaa, baaa, bbaa, bbba and bbbb; nulliplex to quadruplex).

Results

We present a novel algorithm, implemented in the R package fitTetra, to assign genotypes for bi-allelic markers to tetraploid samples from genotyping assays that produce intensity signals for both alleles. The algorithm is based on the fitting of several mixture models with five components, one for each of the five possible genotypes. The models have different numbers of parameters specifying the relation between the five component means, and some of them impose a constraint on the mixing proportions to conform to Hardy-Weinberg equilibrium (HWE) ratios. The software rejects markers that do not allow a reliable genotyping for the majority of the samples, and it assigns a missing score to samples that cannot be scored into one of the five possible genotypes with sufficient confidence.

Conclusions

We have validated the software with data of a collection of 224 potato varieties assayed with an Illumina GoldenGate™ 384 SNP array and shown that all SNPs with informative ratio distributions are fitted. Almost all fitted models appear to be correct based on visual inspection and comparison with diploid samples. When the collection of potato varieties is analyzed as if it were a population, almost all markers seem to be in Hardy-Weinberg equilibrium. The R package fitTetra is freely available under the GNU Public License from http://www.plantbreeding.wur.nl/UK/software_fitTetra.html and as Additional files with this article.

SUBMITTER: Voorrips RE

PROVIDER: S-EPMC3121645 | biostudies-literature | 2011 May

REPOSITORIES: biostudies-literature

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Publications

Genotype calling in tetraploid species from bi-allelic marker data using mixture models.

Voorrips Roeland E RE Gort Gerrit G Vosman Ben B

BMC bioinformatics 20110519

<h4>Background</h4>Automated genotype calling in tetraploid species was until recently not possible, which hampered genetic analysis. Modern genotyping assays often produce two signals, one for each allele of a bi-allelic marker. While ample software is available to obtain genotypes (homozygous for either allele, or heterozygous) for diploid species from these signals, such software is not available for tetraploid species which may be scored as five alternative genotypes (aaaa, baaa, bbaa, bbba ...[more]

PMID: 21595880

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Project description:Recessive SH3TC2 variants cause Charcot-Marie-Tooth disease type 4C (CMT4C). CMT4C is typically a sensorimotor demyelinating polyneuropathy, marked by early onset spinal deformities, but its clinical characteristics and severity are quite variable. Clear relationships between pathogenic variants and the spectrum of disease manifestations are to date lacking. Gene replacement therapy has been shown to ameliorate the phenotype in a mouse model of CMT4C, emphasizing the need for natural history studies to inform clinical trial readiness. Data, including both genetic information and clinical characteristics, were compiled from the longitudinal, prospective dataset of the Inherited Neuropathy Consortium, a member of the Rare Diseases Clinical Research Network (INC-RDCRN). The Charcot Marie Tooth Neuropathy Score (CMTNS), Examination Score (CMTES) and the Rasch-weighted CMTES (CMTES-R) were used to describe symptoms, neurological examinations and neurophysiological characteristics. Standardized response means were calculated at yearly intervals and a mixed model for repeated measures was used to estimate the change in CMTES and CMTES-R over time. Fifty-six individuals (59% female), median age 27 years (range 2-67 years) with homozygous or compound heterozygous variants in SH3TC2 were identified, including 34 unique variants, 14 of which have not previously been published. Twenty-eight participants had longitudinal data available. While there was no significant difference in the CMTES in those with protein truncating versus non-protein truncating variants, there were significant differences in the mean ulnar nerve compound muscle action potential amplitude, the mean radial sensory nerve action potential amplitude, and in the prevalence of scoliosis, suggesting the possibility of a milder phenotype in individuals with one or two non-protein-truncating variants. Overall, the mean value of the CMTES was 13, reflecting moderate clinical severity. There was a high rate of scoliosis (81%), scoliosis surgery (36%), and walking difficulty (94%) among study participants. The CMTES and CMTES-R appeared moderately responsive to change over extended follow-up, demonstrating a standardized response mean of 0.81 standard deviation units or 0.71 standard deviation units, respectively, over 3 years. Our analysis represents the largest cross-sectional and only longitudinal study to date, of the clinical phenotype of both adults and children with CMT4C. With the promise of upcoming genetic treatments, these data will further define the natural history of the disease and inform study design in preparation for clinical trials.

Dataset Information

Genotype calling in tetraploid species from bi-allelic marker data using mixture models.

Background

Results

Conclusions

Publications

Genotype calling in tetraploid species from bi-allelic marker data using mixture models.

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