Relationship of ORP/SRP with good barcode reads for eight double-enzyme combinations.

<p><b>A)</b> The function of unit sequencing cost of fragments was calculated by plotting sequencing depth versus fragment counts. The ORP was defined as the minimum value of the unit sequencing cost (the minimum value of the black-dashed line). <b>B)</b> The sequencing reads of three individuals were sampled at five thresholds (10%, 20%, 50%, 80%, and 100%, respectively). The sequencing depth (green) was equal to the good barcode read numbers divided by the fragment counts. The SRP was the corresponding good barcode reads when the slope of the fragment counts (orange curve) reduced to zero.</p

Number of SNPs by region.

<p>Number of SNPs by region.</p

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

<div><p>High-density single nucleotide polymorphism (SNP) markers are crucial to improve the resolution and accuracy of genome-wide association study (GWAS) and genomic selection (GS). Numerous approaches, including whole genome sequencing, genome sampling sequencing, and SNP chips are able to discover or genotype markers at different densities and costs. Achieving an optimal balance between sequencing resolution and budgets, especially in large-scale population genetics research, constitutes a major challenge. Here, we performed improved double-enzyme digestion genotyping by sequencing (ddGBS) on chicken. We evaluated eight double-enzyme digestion combinations, and <i>Eco</i>R I- <i>Mse</i> I was chosen as the optimal combination for the chicken genome. We firstly proposed that two parameters, optimal read-count point (ORP) and saturated read-count point (SRP), could be utilized to determine the optimal sequencing volume. A total of 291,772 high-density SNPs from 824 animals were identified. By validation using the SNP chip, we found that the consistency between ddGBS data and the SNP chip is over 99%. The approach that we developed in chickens, which is high-quality, high-density, cost-effective (300 K, $30/sample), and time-saving (within 48 h), will have broad applications in animal breeding programs.</p></div

Genotyping accuracy evaluation according to different sequencing depths.

<p><b>A)</b> Distribution of coverage depths for all SNPs. <b>B)</b> Consistency of ddGBS genotyping results compared with 60K BeadArray microarrays using various filter conditions (sequencing depth ranging from 2× to 12×). <b>C)</b> Comparison of the missing rates of all 292 K SNPs on a per-site basis before and after depth filtering of 5×. <b>D)</b> Comparison of the missing rates of all 824 samples on a per-individual basis before and after depth filtering of 5×.</p

Results of both <i>in silico</i> analysis and empirical evidence of enzyme digestions.

<p>A) Fragment size distribution obtained by <i>in silico</i> digestion of the chicken genome with different double-enzyme combinations. B) Single-enzyme and double-enzyme digestion for 2 h or 12 h.</p

Summary of parameters among different combinations.

<p>Summary of parameters among different combinations.</p

Distribution of CV_depth for each combination.

<p>Distribution of CV_depth for all fragments in each combination is displayed via boxplot. Lower and upper boundary lines of the boxes represent the 25%/75% quantile of CV_depth, and the central lines indicate the median of the data. The upper and lower whiskers represent scores outside the middle 50%. The number in each box indicate the mean of CV_depth for all fragments±standard deviation (SD).</p

LD decay of the advanced intercross chicken lines.

<p>A squared allelic correlation coefficient (r²) against the distance between the SNPs in the F₀ generation (HQLA was depicted as the green line, and HB was depicted as the red line) and F₉ generation (the blue line).</p

Distribution of SNPs discovered from three individuals across chromosomes.

<p>Distribution of SNPs discovered from three individuals across chromosomes.</p

Statistics of sequenced three samples from different combinations.

<p>Statistics of sequenced three samples from different combinations.</p