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Using genotyping-by-sequencing to predict gender in animals.

ABSTRACT: Gender assignment errors are common in some animal species and lead to inaccuracies in downstream analyses. Procedures for detecting gender misassignment are available for array-based SNP data but are still being developed for genotyping-by-sequencing (GBS) data. In this study, we describe a method for using GBS data to predict gender using X and Y chromosomal SNPs. From a set of 1286 X chromosomal and 23 Y chromosomal deer (Cervus sp.) SNPs discovered from GBS sequence reads, a prediction model was built using a training dataset of 422 Red deer and validated using a test dataset of 868 Red deer and Wapiti deer. Prediction was based on the proportion of heterozygous genotypes on the X chromosome and the proportion of non-missing genotypes on the Y chromosome observed in each individual. The concordance between recorded gender and predicted gender was 98.6% in the training dataset and 99.3% in the test dataset. The model identified five individuals across both datasets with incorrect recorded gender and was unable to predict gender for another five individuals. Overall, our method predicted gender with a high degree of accuracy and could be used for quality control in gender assignment datasets or for assigning gender when unrecorded, provided a suitable reference genome is available.

SUBMITTER: Bilton TP

PROVIDER: S-EPMC6593676 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Using genotyping-by-sequencing to predict gender in animals.

Bilton T P TP Chappell A J AJ Clarke S M SM Brauning R R Dodds K G KG McEwan J C JC Rowe S J SJ

Animal genetics 20190407 3

Gender assignment errors are common in some animal species and lead to inaccuracies in downstream analyses. Procedures for detecting gender misassignment are available for array-based SNP data but are still being developed for genotyping-by-sequencing (GBS) data. In this study, we describe a method for using GBS data to predict gender using X and Y chromosomal SNPs. From a set of 1286 X chromosomal and 23 Y chromosomal deer (Cervus sp.) SNPs discovered from GBS sequence reads, a prediction model ...[more]

PMID: 30957265

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Project description:BackgroundUnderstanding the dynamics of gametocyte production in polyclonal Plasmodium falciparum infections requires a genotyping method that detects distinct gametocyte clones and estimates their relative frequencies. Here, a marker was identified and evaluated to genotype P. falciparum mature gametocytes using amplicon deep sequencing.MethodsA data set of polymorphic regions of the P. falciparum genome was mined to identify a gametocyte genotyping marker. To assess marker resolution, the number of unique haplotypes in the marker region was estimated from 95 Malawian P. falciparum whole genome sequences. Specificity of the marker for detection of mature gametocytes was evaluated using reverse transcription-polymerase chain reaction of RNA extracted from NF54 mature gametocytes and rings from a non-gametocyte-producing strain of P. falciparum. Amplicon deep sequencing was performed on experimental mixtures of mature gametocytes from two distinct parasite clones, as well as gametocyte-positive P. falciparum field isolates to evaluate the quantitative ability and determine the limit of detection of the genotyping approach.ResultsA 400 bp region of the pfs230 gene was identified as a gametocyte genotyping marker. A larger number of unique haplotypes was observed at the pfs230 marker (34) compared to the sera-2 (18) and ama-1 (14) markers in field isolates from Malawi. RNA and DNA genotyping accurately estimated gametocyte and total parasite clone frequencies when evaluating agreement between expected and observed haplotype frequencies in gametocyte mixtures, with concordance correlation coefficients of 0.97 [95% CI: 0.92-0.99] and 0.92 [95% CI: 0.83-0.97], respectively. The detection limit of the genotyping method for male gametocytes was 0.41 pfmget transcripts/µl [95% CI: 0.28-0.72] and for female gametocytes was 1.98 ccp4 transcripts/µl [95% CI: 1.35-3.68].ConclusionsA region of the pfs230 gene was identified as a marker to genotype P. falciparum gametocytes. Amplicon deep sequencing of this marker can be used to estimate the number and relative frequency of parasite clones among mature gametocytes within P. falciparum infections. This gametocyte genotyping marker will be an important tool for studies aimed at understanding dynamics of gametocyte production in polyclonal P. falciparum infections.

Project description:Soybean (Glycine max) breeding involves improving commercially grown varieties by introgressing important agronomic traits from poor yielding accessions and/or wild relatives of soybean while minimizing the associated yield drag. Molecular markers associated with these traits are instrumental in increasing the efficiency of producing such crosses and Single Nucleotide Polymorphisms (SNPs) are particularly well suited for this task, owing to high density in the non-genic regions and thus increased likelihood of finding a tightly linked marker to a given trait. A rapid method to develop SNP markers that can differentiate specific loci between any two parents in soybean is thus highly desirable. In this study we investigate such a protocol for developing SNP markers between multiple soybean accessions and the reference Williams 82 genome. To restrict sampling frequency reduced representation libraries (RRLs) of genomic DNA were generated by restriction digestion followed by library construction. We chose to sequence four accessions Dowling (PI 548663), Dwight (PI 597386), Komata (PI200492) and PI 594538A for their agronomic importance as well as Williams 82 as a control.MseI was chosen to digest genomic DNA based on predictions that it will cut sparingly in the mathematically defined high-copy-number regions of the genome. All RRLs were sequenced on the Illumina genome analyzer. Reads were aligned to the Glyma1 reference assembly and SNP calls made from the alignments. We identified from 4294 to 14550 SNPs between the four accessions and the Williams 82 reference. In addition a small number of SNPs (1142) were found by aligning Williams 82 reads to the reference assembly (Glyma1) suggesting limited genetic variation within the Williams 82 line. The SNP data allowed us to estimate genetic diversity between the four lines and Williams 82. Restriction digestion of soybean genomic DNA with MseI followed by high throughput sequencing provides a rapid and reproducible method for generating SNP markers.

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Using genotyping-by-sequencing to predict gender in animals.

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Using genotyping-by-sequencing to predict gender in animals.

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