A genome-wide assessment of conserved SNP alleles reveals a panel of regulatory SNPs relevant to the peripheral nerve

A Panel of rSNPs Demonstrating Allelic Asymmetry in Both ChIP-seq and RNA-seq Data and the Search for Their Phenotypic Outcomes through Analysis of DEGs

Currently, the detection of the allele asymmetry of gene expression from RNA-seq data or the transcription factor binding from ChIP-seq data is one of the approaches used to identify the functional genetic variants that can affect gene expression (regulatory SNPs or rSNPs). In this study, we searched for rSNPs using the data for human pulmonary arterial endothelial cells (PAECs) available from the Sequence Read Archive (SRA). Allele-asymmetric binding and expression events are analyzed in paired ChIP-seq data for H3K4me3 mark and RNA-seq data obtained for 19 individuals. Two statistical approaches, weighted z-scores and predicted probabilities, were used to improve the efficiency of finding rSNPs. In total, we identified 14,266 rSNPs associated with both allele-specific binding and expression. Among them, 645 rSNPs were associated with GWAS phenotypes; 4746 rSNPs were reported as eQTLs by GTEx, and 11,536 rSNPs were located in 374 candidate transcription factor binding motifs. Additionally, we searched for the rSNPs associated with gene expression using an SRA RNA-seq dataset for 281 clinically annotated human postmortem brain samples and detected eQTLs for 2505 rSNPs. Based on these results, we conducted Gene Ontology (GO), Disease Ontology (DO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and constructed the protein-protein interaction networks to represent the top-ranked biological processes with a possible contribution to the phenotypic outcome.

A new SNP genotyping technology Target SNP-seq and its application in genetic analysis of cucumber varieties

To facilitate the utility of SNP-based genotyping, we developed a new method called target SNP-seq which combines the advantages of multiplex PCR amplification and high throughput sequencing. Compared with KASP, Microarrays, GBS and other SNP genotyping methods, target SNP-seq is flexible both in SNPs and samples, yields high accuracy, especially when genotyping genome wide perfect SNPs with high polymorphism and conserved flanking sequences, and is cost-effective, requiring 3 days and $7 for per DNA sample to genotype hundreds of SNP loci. The present study established a DNA fingerprint of 261 cucumber varieties by target SNP-seq with 163 perfect SNPs from 4,612,350 SNPs based on 182 cucumber resequencing datasets. Four distinct subpopulations were found in 261 Chinese cucumber varieties: the north China type, the south China type, the Europe type, and the Xishuangbanna type. The north China type and Xishuangbanna type harbored lower genetic diversity, indicating greater risk of genetic erosion in these two subpopulations. Furthermore, a core set of 24 SNPs was able to distinguish 99% of the 261 cucumber varieties. 29 core cucumber backbone varieties in China were identified. Therefore, target SNP-seq provides a new way to screen out core SNP loci from the whole genome for DNA fingerprinting of crop varieties. The high efficiency and low cost of target SNP-seq is more competitive than the current SNP genotyping methods, and it has excellent application prospects in genetic research, as well as in promoting plant breeding processes in the near future.