Dataset Information

Evaluation of SNP Genotyping in Alpacas Using the Bovine HD Genotyping Beadchip.

ABSTRACT: Alpacas are one of four South American Camelid species living in the highlands of the Andes. Production of alpaca fiber contributes to the economy of the region and the livelihood of many rural families. Fiber quantity and quality are important and in need of a modern breeding program based on genomic selection to accelerate genetic gain. To achieve this is necessary to discover enough molecular markers, single nucleotide polymorphisms (SNPs) in particular, to provide genome coverage and facilitate genome wide association studies to fiber production characteristics. The aim of this study was to discover alpaca SNPs by genotyping forty alpaca DNA samples using the BovineHD Genotyping Beadchip. Data analysis was performed with GenomeStudio (Illumina) software. Because different filters and thresholds are reported in the literature we investigated the effects of no-call threshold (?0.05, ?0.15, and ?0.25) and call frequency (?0.9 and =1.0) in identifying positive SNPs. Average GC Scores, calculated as the average of the 10% and 50% GenCall scores for each SNP (?0.70) and the GenTrain score ? 0.25 parameters were applied to all comparisons. SNPs with minor allele frequency (MAF) ? 0.05 or ? 0.01 were retained. Since detection of SNPs is based on the stable binding of oligonucleotide probes to the target DNA immediately adjacent to the variant nucleotide, all positive SNP flanking sequences showing perfect alignments between the bovine and alpaca genomes for the first 21 or 26 nucleotides flanking the variant nucleotide at either side were selected. Only SNPs localized in one scaffold were assumed unique. Unique SNPs identified in both reference genomes were kept and mapped on the Vicugna_pacos 2.0.2 genome. The effects of the no-call threshold ? 0.25, call frequency = 1 and average GC ? 0.7 were meaningful and identified 6756 SNPs of which 400 were unique and polymorphic (MAF ? 0.01). Assignment to alpaca chromosomes was possible for 292 SNPs. Likewise, 209 SNPs were localized in 202 alpaca gene loci and 29 of these share the same loci with the dromedary. Interestingly, 69 of 400 alpaca SNPs have 100% similarity with dromedary.

SUBMITTER: More M

PROVIDER: S-EPMC6492526 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Evaluation of SNP Genotyping in Alpacas Using the Bovine HD Genotyping Beadchip.

More Manuel M Gutiérrez Gustavo G Rothschild Max M Bertolini Francesca F Ponce de León F Abel FA

Frontiers in genetics 20190424

Alpacas are one of four South American Camelid species living in the highlands of the Andes. Production of alpaca fiber contributes to the economy of the region and the livelihood of many rural families. Fiber quantity and quality are important and in need of a modern breeding program based on genomic selection to accelerate genetic gain. To achieve this is necessary to discover enough molecular markers, single nucleotide polymorphisms (SNPs) in particular, to provide genome coverage and facilit ...[more]

PMID: 31105741

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Project description:BACKGROUND: In recent years, genome-wide association studies have successfully uncovered single-nucleotide polymorphisms (SNPs) associated with complex traits such as diseases and quantitative phenotypes. These variations account for a small proportion of heritability. With the development of high throughput techniques, abundant submicroscopic structural variations have been found in organisms, of which the main variations are copy number variations (CNVs). Therefore, CNVs are increasingly recognized as an important and abundant source of genetic variation and phenotypic diversity. RESULTS: Analyses of CNVs in the genomes of three sheep breeds were performed using the Ovine SNP50 BeadChip array. A total of 238 CNV regions (CNVRs) were identified, including 219 losses, 13 gains, and six with both events (losses and gains), which cover 60.35 Mb of the sheep genomic sequence and correspond to 2.27% of the autosomal genome sequence. The length of the CNVRs on autosomes range from 13.66 kb to 1.30 Mb with a mean size of 253.57 kb, and 75 CNVRs events had a frequency > 3%. Among these CNVRs, 47 CNVRs identified by the PennCNV overlapped with the CNVpartition. Functional analysis indicated that most genes in the CNVRs were significantly enriched for involvement in the environmental response. Furthermore, 10 CNVRs were selected for validation and 6 CNVRs were further experimentally confirmed by qPCR. In addition, there were 57 CNVRs overlapped in our new dataset and other published ruminant CNV studies. CONCLUSIONS: In this study, we firstly constructed a sheep CNV map based on the Ovine SNP50 array. Our results demonstrated the differences of two detection tools and integration of multiple algorithms can enhance the detection of sheep genomic structure variations. Furthermore, our findings would be of help for understanding the sheep genome and provide preliminary foundation for carrying out the CNVs association studies with economically important phenotypes of sheep in the future.

Project description:Highly specific amplification of complex DNA pools without bias or template-independent products (TIPs) remains a challenge. We have developed a procedure using phi29 DNA polymerase and trehalose and optimized control of amplification to create micrograms of specific amplicons without TIPs from down to sub-femtograms of DNA. The amplicons from 5 ng and 0.5 ng DNA, which were from originally good quality of gDNA (05-050), or partially degraded gDNA (04-018), were validate with Illumina HumanHap550-Duo Genotyping Beadchip. As seen in (Suppl. Table 5a), the call rates (97.30% to 99.07%) and accuracy or concordance ( > 99.85% for the SNPs called in both amplicon and natural reference) for 5 ng derived amplicons with both Wpa and Gv2 were close to each other and close to native gDNA (call rate: 98.3% to 99.75%). These call rates were better than a recent report (amplicon 95.9% vs. un-amplified 98.5%), in which the early kit Repli-g 625S was applied, and re-genotyping was performed when the performance was low and duplicate samples were filtered for the highest call rate. The genotyping accuracy of Wpa was actually in the same range as the variation in technical replicates with similar SNP typing arrays (99.87% and 99.88%, replicated Affymetrix array, or between Affymetrix and Illumina arrays). Importantly, the genotyping concordance for amplicons generated from 0.5 ng with Wpa (99.88% and 99.69%) were also close to the technical replicates. In this case, the call rates of Wpa were slightlyreduced compared to that with 5 ng input, but the call rate for the partially degraded sample 04-018, was modestly improved over Gv2 (92.06 % vs. 90.53%). Wpa data also showed some amplification non-uniformity among different locations, resulting in some “artificial CNVs” similar to Gv2 (exampled as in Suppl. Fig. 5 and Suppl. Table 6), with the outputs obtained by taking unamplified gDNAs as their reference. This imbalance however was consistent and reproducible for each method but different between Wpa and Gv2. These artificial CNVs can be efficiently cancelled if pair-wise amplified test and reference are compared, as observed in CGH result (Fig. 4 and Suppl. Fig. 4), also supported by others {Pugh 2008}. It is interesting to note that the representation of chromosomal terminal sequences was greatly improved with Wpa compared with Gv2 (Fig. 5), and that some of these regions were significantly under-amplified or even lost with Gv2 (Suppl. Fig. 5 and Suppl. Table 6, 7), as also independently reported recently {Pugh 2008}. This occurred especially in the terminal 3 to 5 Mb and sometimes extended to 10 Mb in many chromosome termini, and was particularly serious when low levels or degraded DNA was as input. An analysis for 5 Mb termini is shown (Suppl. Table 5b calculated all involved SNPs as a cohort. Fig. 5 and Suppl. Tables 6 and 7 were the result for each chromosome terminus). Importantly, the SNP typing was also greatly improved, outstandingly exemplified by the amplicons of 0.5 ng input for the partially degraded 04-018, with Wpa versus Gv2 call rate of 91.9% vs. 84.45% and accuracy of 99.57% vs. 98.62%. The result also showed that these terminal regions underrepresentation in Gv2 was not absolutely associated with the distance-to-end, but possibly was a sequence related issue. Keywords: Whole-pool amplification, whole genome SNP typing

Dataset Information

Evaluation of SNP Genotyping in Alpacas Using the Bovine HD Genotyping Beadchip.

Publications

Evaluation of SNP Genotyping in Alpacas Using the Bovine HD Genotyping Beadchip.

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