Optimized double-digest genotyping by sequencing (ddGBS) method with high-density SNP markers and high genotyping accuracy for chickens

Wang, Yuzhe; Cao, Xianglin; Zhao, Yaofeng; Jing, Fei; Hu, Xiaoxiang; Li, Ning

doi:10.1371/journal.pone.0179073

Cited by 31 publications

(38 citation statements)

References 49 publications

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“…Multiple studies have speculated and tested the impact of different parameter settings on pre- and post-sequencing procedures of RAD-based protocols, especially in loci reconstruction summary statistics, i.e number of loci or SNPs, or heterozygosity (Davey et al, 2013; Gautier et al, 2013; K. Andrews & Luikart, 2014; K. R. Andrews et al, 2014; Puritz et al, 2014; Mastretta-Yanes et al, 2015; Burns et al, 2017; Rochette & Catchen, 2017; Y. Wang et al, 2017; Willis et al, 2017). Nevertheless, only a handful of them linked those parameters to the downstream biological interpretation (Mastretta-Yanes et al, 2015; Rodríguez-Ezpeleta et al, 2016; Shafer et al, 2017; Malinsky et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

“…Concerning the dry protocol, an important part of the RAD-based sequencing literature pertains to the bioinformatic treatment of sequences and to loci reconstruction (Mastretta-Yanes et al, 2015; Paris et al, 2017; Rochette & Catchen, 2017; Y. Wang et al, 2017). These studies highlight the impact of clustering thresholds ( e.g.…”

Section: Discussionmentioning

confidence: 99%

“…Indeed, these thresholds have been shown to influence the number of recovered loci, coverage, number of identified SNPs and error rates (Mastretta-Yanes et al, 2015; Paris et al, 2017; Rochette & Catchen, 2017; Y. Wang et al, 2017). In agreement with previous works, we found a substantial impact of the minimum coverage ( m ) and clustering ( M ) thresholds on ddRADseq loci recovery and reconstruction during the bioinformatic process.…”

Section: Discussionmentioning

confidence: 99%

“…For example, this choice will influence the number of digested fragments, their location in the genome, and their size distribution (Burns et al, 2017; Y. Wang et al, 2017). DNA quality also influences SNPs recovery, because degraded ( i.e.…”

Section: Introductionmentioning

confidence: 99%

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Double-digest RAD-sequencing: do wet and dry protocol parameters impact biological results?

Cumer

Pouchon

Boyer

et al. 2018

Preprint

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1 2 1 3 Running headline: 1 4 Impact of wet and dry protocol of ddRAD-seq 1 5 1 6 2 ABSTRACT 1 7 1 81. Next-generation sequencing technologies have opened a new era of research in genomics. 9Among these, restriction enzyme-based techniques such as restriction-site associated DNA 2 0 sequencing (RADseq) or double-digest RAD-sequencing (ddRADseq) are now widely used in 2 1 many population genomics fields. From DNA sampling to SNP calling, both wet and dry 2 2 protocols have been discussed in the literature to identify key parameters for an optimal loci 2 3 reconstruction. 2 4 2. The impact of these parameters on downstream analyses and biological results drawn from 2 5RADseq or ddRADseq data has however not been fully explored yet. In this study, we tackled 2 6 this issue by investigating the effects of ddRADseq laboratory (i.e. wet protocol) and 2 7 bioinformatics (i.e. dry protocol) settings on loci reconstruction and inferred biological signal 2 8 at two evolutionary scale using two systems: a complex of butterfly species (Coenonympha 2 9 sp.) and populations of Common beech (Fagus sylvatica). 3 0 3. Results suggest an impact of wet protocol parameters (DNA quantity, number of PCR 3 1 cycles during library preparation) on the number of recovered reads and SNPs, the number of 3 2unique alleles and individual heterozygosity. We also found that bioinformatic settings (i.e. 3 3 clustering and minimum coverage thresholds) impact loci reconstruction (e.g. number of loci, 3 4mean coverage) and SNP calling (e.g. number of SNPs, heterozygosity). We however do not 3 5 detect an impact of parameter settings on three types of analysis performed with ddRADseq 3 6 data: measure of genetic differentiation, estimation of individual admixture, and demographic 3 7inferences. In addition, our work demonstrates the high reproducibility and low rate of 3 8

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Double-digest RAD-sequencing: do wet and dry protocol parameters impact biological results?

Cumer

Pouchon

Boyer

et al. 2018

Preprint

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“…NGS-based genotyping methods are capable of simultaneously genotyping markers on a genome-wide scale, even in nonmodel species with little or no available genetic information (Torkamaneh et al, 2018a). NGS-based reduced-representation sequencing (RRS) strategies [restriction site-associated DNA sequencing (RAD-seq), complexity reduction of polymorphic sequences (CRoPS), genotyping-bysequencing (GBS), double-digest RAD-seq (ddRAD), 2bRAD, and double-digest GBS (ddGBS)], relying on high-throughput sequencing (HTS) of multiplexed samples, allows for the genotyping of thousands to millions of SNPs in parallel in large sets of individual samples (Baird et al, 2008;Elshire et al, 2011;Davey et al, 2011;Peterson et al, 2012;Wang et al, 2012;Ali et al, 2016;Wang et al, 2017). The RRS methods all follow similar DNA library preparation steps (DNA digestion, adaptor ligation, amplification, and sequencing) and are generically called GBS.…”

Section: Introductionmentioning

confidence: 99%

NanoGBS: A Miniaturized Procedure for GBS Library Preparation

et al. 2020

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High-throughput reduced-representation sequencing (RRS)-based genotyping methods, such as genotyping-by-sequencing (GBS), have provided attractive genotyping solutions in numerous species. Here, we present NanoGBS, a miniaturized and eco-friendly method for GBS library construction. Using acoustic droplet ejection (ADE) technology, NanoGBS libraries were constructed in tenfold smaller volumes compared to standard methods (StdGBS) and leading to a reduced use of plastics of up to 90%. A high-quality DNA library and SNP catalogue were obtained with extensive overlap (96%) in SNP loci and 100% agreement in genotype calls compared to the StdGBS dataset with a high level of accuracy (98.5%). A highly multiplexed pool of GBS libraries (768-plex) was sequenced on a single Ion Proton PI chip and yielded enough SNPs (~4K SNPs; 1.5 SNP per cM, on average) for many high-volume applications. Combining NanoGBS library preparation and increased multiplexing can dramatically reduce (72%) genotyping cost per sample. We believe that this approach will greatly facilitate the adoption of marker applications where extremely high throughputs are required and cost is still currently limiting.

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Genome-wide association study of bone mineral density trait among three pig breeds

Jiang

Wang

Tang

et al. 2020

Animal

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Leg weakness (LW) issues are a great concern for pig breeding industry. And it also has a serious impact on animal welfare. To dissect the genetic architecture of limb-and-hoof firmness in commercial pigs, a genome-wide association study was conducted on bone mineral density (BMD) in three sow populations, including Duroc, Landrace and Yorkshire. The BMD data were obtained by ultrasound technology from 812 pigs (including Duroc 115, Landrace 243 and Yorkshire 454). In addition, all pigs were genotyped using genome-by-sequencing and a total of 224 162 single-nucleotide polymorphisms (SNPs) were obtained. After quality control, 218 141 SNPs were used for subsequent genome-wide association analysis. Nine significant associations were identified on chromosomes 3, 5, 6, 7, 9, 10, 12 and 18 that passed Bonferroni correction threshold of 0.05/(total SNP numbers). The most significant locus that associated with BMD (P value = 1.92e−14) was detected at approximately 41.7 Mb on SSC6 (SSC stands for Sus scrofa chromosome). CUL7, PTK7, SRF, VEGFA, RHEB, PRKAR1A and TPO that are located near the lead SNP of significant loci were highlighted as functionally plausible candidate genes for sow limb-and-hoof firmness. Moreover, we also applied a new method to measure the BMD data of pigs by ultrasound technology. The results provide an insight into the genetic architecture of LW and can also help to improve animal welfare in pigs.

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Optimized double-digest genotyping by sequencing (ddGBS) method with high-density SNP markers and high genotyping accuracy for chickens

Cited by 31 publications

References 49 publications

Double-digest RAD-sequencing: do wet and dry protocol parameters impact biological results?

Double-digest RAD-sequencing: do wet and dry protocol parameters impact biological results?

NanoGBS: A Miniaturized Procedure for GBS Library Preparation

Genome-wide association study of bone mineral density trait among three pig breeds

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