High-quality Single Nucleotide Variants Research Articles

Identification of quantitative trait loci (QTLs) and candidate genes of seed Iron and zinc content in soybean [Glycine max (L.) Merr.

BackgroundDeciphering the hereditary mechanism of seed iron (Fe) and zinc (Zn) content in soybean is important and sustainable to address the “hidden hunger” that presently affects approximately 2 billion people worldwide. Therefore, in order to detect genomic regions related to soybean seed Fe and Zn content, a recombinant inbred line (RIL) population with 248 lines was assessed in four environments to detect Quantitative Trait Loci (QTLs) related to soybean seed Fe and Zn content.ResultWide variation was found in seed Fe and Zn content in four environments, and genotype, environment, and genotype × environment interactions had significant influences on both the seed Fe and Zn content. A positive correlation was observed between seed Fe content and seed Zn content, and broad-sense heritability (H2) of seed Fe and Zn content were 0.73 and 0.75, respectively. In this study, five QTLs for seed Fe content were detected with 4.57 - 32.71% of phenotypic variation explained (PVE) and logarithm of odds (LOD) scores ranging from 3.60 to 33.79. Five QTLs controlling the seed Zn content were detected, and they individually explained 3.35 to 26.48% of the phenotypic variation, with LOD scores ranging from 3.64 to 20.4. Meanwhile, 409,541 high-quality single-nucleotide variants (SNVs) and 85,102 InDels (except intergenic regions) between two bi-parental lines were identified by whole genome resequencing. A total of 12 candidate genes were reported in one major QTL for seed Fe content and two major QTLs for seed Zn content, with the help of RNA-Seq analysis, gene ontology (GO) enrichment, gene annotation, and bi-parental whole genome sequencing (WGS) data.ConclusionsLimited studies were performed about microelement of soybean, so these results may play an important role in the biofortification of Fe and Zn and accelerate the development of marker-assisted selection (MAS) for breeding soybeans fortified with iron and zinc.

Haplotype-aware variant calling with PEPPER-Margin-DeepVariant enables high accuracy in nanopore long-reads.

Long-read sequencing has the potential to transform variant detection by reaching currently difficult-to-map regions and routinely linking together adjacent variations to enable read based phasing. Third-generation nanopore sequence data has demonstrated a long read length, but current interpretation methods for its novel pore-based signal have unique error profiles, making accurate analysis challenging. Here, we introduce a haplotype-aware variant calling pipeline PEPPER-Margin-DeepVariant that produces state-of-the-art variant calling results with nanopore data. We show that our nanopore-based method outperforms the short-read-based single nucleotide variant identification method at the whole genome-scale and produces high quality single nucleotide variants in segmental duplications and low-mappability regions where short-read based genotyping fails. We show that our pipeline can provide highly-contiguous phase blocks across the genome with nanopore reads, contiguously spanning between 85% to 92% of annotated genes across six samples. We also extend PEPPER-Margin-DeepVariant to PacBio HiFi data, providing an efficient solution with superior performance than the current WhatsHap-DeepVariant standard. Finally, we demonstrate de novo assembly polishing methods that use nanopore and PacBio HiFi reads to produce diploid assemblies with high accuracy (Q35+ nanopore-polished and Q40+ PacBio-HiFi-polished).

Ionizing Radiation Alters the Transition/Transversion Ratio in the Exome of Human Gingiva Fibroblasts.

Little is known about the mutational impact of ionizing radiation (IR) exposure on a genome-wide level in mammalian tissues. Recent advancements in sequencing technology have provided powerful tools to perform exome-wide analyses of genetic variation. This also opened up new avenues for studying and characterizing global genomic IR-induced effects. However, genotypes generated by next generation sequencing (NGS) studies can contain errors, which may significantly impact the power to detect signals in common and rare variant analyses. These genotyping errors are not explicitly detected by the standard Genotype Analysis ToolKit (GATK) and Variant Quality Score Recalibration (VQSR) tool and thus remain a potential source of false-positive variants in whole exome sequencing (WES) datasets. In this context, the transition-transversion ratio (Ti/Tv) is commonly used as an additional quality check. In case of IR experiments, this is problematic when Ti/Tv itself might be influenced by IR treatment. It was the aim of this study to determine a suitable threshold for variant filters for NGS datasets from irradiated cells in order to achieve high data quality using Ti/Tv, while at the same time being able to investigate radiation-specific effects on the Ti/Tv ratio for different radiation doses. By testing a variety of filter settings and comparing the obtained results with publicly available datasets, we observe that a coverage filter setting of depth (DP) 3 and genotype quality (GQ) 20 is sufficient for high quality single nucleotide variants (SNVs) calling in an analysis combining GATK and VSQR and that Ti/Tv values are a consistent and useful indicator for data quality assessment for all tested NGS platforms. Furthermore, we report a reduction in Ti/Tv in IR-induced mutations in primary human gingiva fibroblasts (HGFs), which points to an elevated proportion of transversions among IR-induced SNVs and thus might imply that mismatch repair (MMR) plays a role in the cellular damage response to IR-induced DNA lesions.

MACSNVdb: a high-quality SNV database for interspecies genetic divergence investigation among macaques.

Macaques are the most widely used non-human primates in biomedical research. The genetic divergence between these animal models is responsible for their phenotypic differences in response to certain diseases. However, the macaque single nucleotide polymorphism resources mainly focused on rhesus macaque (Macaca mulatta), which hinders the broad research and biomedical application of other macaques. In order to overcome these limitations, we constructed a database named MACSNVdb that focuses on the interspecies genetic diversity among macaque genomes. MACSNVdb is a web-enabled database comprising ~74.51 million high-quality non-redundant single nucleotide variants (SNVs) identified among 20 macaque individuals from six species groups (muttla, fascicularis, sinica, arctoides, silenus, sylvanus). In addition to individual SNVs, MACSNVdb also allows users to browse and retrieve groups of user-defined SNVs. In particular, users can retrieve non-synonymous SNVs that may have deleterious effects on protein structure or function within macaque orthologs of human disease and drug-target genes. Besides position, alleles and flanking sequences, MACSNVdb integrated additional genomic information including SNV annotations and gene functional annotations. MACSNVdb will facilitate biomedical researchers to discover molecular mechanisms of diverse responses to diseases as well as primatologist to perform population genetic studies. We will continue updating MACSNVdb with newly available sequencing data and annotation to keep the resource up to date. Database URL: http://big.cdu.edu.cn/macsnvdb/

Genomic adaptation to drought in wild barley is driven by edaphic natural selection at the Tabigha Evolution Slope

Ecological divergence at a microsite suggests adaptive evolution, and this study examined two abutting wild barley populations, each 100 m across, differentially adapted to drought tolerance on two contrasting soil types, Terra Rossa and basalt at the Tabigha Evolution Slope, Israel. We resequenced the genomes of seven and six wild barley genotypes inhabiting the Terra Rossa and basalt soils, respectively, and identified a total of 69,192,653 single-nucleotide variants (SNVs) and insertions/deletions in comparison with a reference barley genome. Comparative genomic analysis between these abutting wild barley populations involved 19,615,087 high-quality SNVs. The results revealed dramatically different selection sweep regions relevant to drought tolerance driven by edaphic natural selection within 2,577 selected genes in these regions, including key drought-responsive genes associated with ABA synthesis and degradation (such as Cytochrome P450 protein) and ABA receptor complex (such as PYL2, SNF1-related kinase). The genetic diversity of the wild barley population inhabiting Terra Rossa soil is much higher than that from the basalt soil. Additionally, we identified different sets of genes for drought adaptation in the wild barley populations from Terra Rossa soil and from wild barley populations from Evolution Canyon I at Mount Carmel. These genes are associated with abscisic acid signaling, signaling and metabolism of reactive oxygen species, detoxification and antioxidative systems, rapid osmotic adjustment, and deep root morphology. The unique mechanisms for drought adaptation of the wild barley from the Tabigha Evolution Slope may be useful for crop improvement, particularly for breeding of barley cultivars with high drought tolerance.

A genome-wide approach to screen for genetic variants in broilers (Gallus gallus) with divergent feed conversion ratio.

Feed conversion ratio (FCR) is an economically important trait in broilers and feed accounts for a significant proportion of the costs involved in broiler production. To explore the contribution of functional variants to FCR trait, we analyzed coding and non-coding single-nucleotide variants (SNVs) across the genome by exome sequencing in seven pairs of full-sibs broilers with divergent FCR and with a sequence coverage at an average depth of fourfold. We identified 192,119 high-quality SNVs, including 30,380 coding SNVs (cSNVs) in the experimental population. We discovered missense SNVs in PGM2, NOX4, TGFBR3, and TMX4, and synonymous SNVs in TSNAX, ITA, HSP90B1, and COL18A1 associated with FCR. Haplotype analyses of genome-wide significant SNVs in PGM2, PHKG1, DGKZ, and SOD2 were also observed with suggestive evidence of haplotype association with FCR. Single-variant and FCR QTL-related genes-based association analyses of SNVs identified newly associated genes for FCR in the regions subjected to targeted exome sequencing. The top seven SNVs were next evaluated in independent replication data sets where SNV chr. 3: 13,990,160 (c. 961G>C) at TMX4 was replicated (p<0.05). Collectively, we have detected SNVs associated with FCR in broiler as well as identification of SNVs in known FCR QTL region. These findings should facilitate the discovery of causative variants for FCR and contribute to marker-assisted selection.

Whole-genome sequencing is more powerful than whole-exome sequencing for detecting exome variants

We compared whole-exome sequencing (WES) and whole-genome sequencing (WGS) in six unrelated individuals. In the regions targeted by WES capture (81.5% of the consensus coding genome), the mean numbers of single-nucleotide variants (SNVs) and small insertions/deletions (indels) detected per sample were 84,192 and 13,325, respectively, for WES, and 84,968 and 12,702, respectively, for WGS. For both SNVs and indels, the distributions of coverage depth, genotype quality, and minor read ratio were more uniform for WGS than for WES. After filtering, a mean of 74,398 (95.3%) high-quality (HQ) SNVs and 9,033 (70.6%) HQ indels were called by both platforms. A mean of 105 coding HQ SNVs and 32 indels was identified exclusively by WES whereas 692 HQ SNVs and 105 indels were identified exclusively by WGS. We Sanger-sequenced a random selection of these exclusive variants. For SNVs, the proportion of false-positive variants was higher for WES (78%) than for WGS (17%). The estimated mean number of real coding SNVs (656 variants, ∼3% of all coding HQ SNVs) identified by WGS and missed by WES was greater than the number of SNVs identified by WES and missed by WGS (26 variants). For indels, the proportions of false-positive variants were similar for WES (44%) and WGS (46%). Finally, WES was not reliable for the detection of copy-number variations, almost all of which extended beyond the targeted regions. Although currently more expensive, WGS is more powerful than WES for detecting potential disease-causing mutations within WES regions, particularly those due to SNVs.

Abstract 4833: A genomic portrait of tumor progression using next-generation sequencing

Abstract Genetic alterations are thought to enable cancers to proliferate and survive more effectively or to resist cytotoxic therapies. However, the molecular basis of tumorigenesis and progression is not fully understood. In order to understand the genetic aberrations underlying tumor progression in refractory neuroblastoma, we performed next-generation sequencing on the whole exomes of three sequential tumor samples taken from a high-risk stage 4 neuroblastoma patient at diagnosis, after cytotoxic therapies, and at death, paired with a germline DNA sample from the same patient. Each genomic DNA sample was first partitioned using SureSelect whole human exome kits targeting ∼38Mb of genomic regions, then subjected to sequencing. Each exome sequencing experiment yielded approximately 240 million mappable reads representing 12 billion base pairs. We used DiBayes to identify single nucleotide variants (SNVs). After filtering away the low-quality SNVs, we identified approximately 18,000 high-quality SNVs in each sample, of which ∼7500 are within the protein coding regions. Using the frequencies of the SNVs derived from the sequencing experiments, we discovered a shared LOH signature at the chromosome level among all three tumors indicating they originate from a common cancer progenitor. When we examined the germline DNA, we found about 97% of SNVs for each tumor sample were also found in the germline DNA, and each tumor had more than 300 unique somatic SNVs. These data showed that despite of the shared LOH pattern, tumor genomes are highly unstable at the single nucleotide level. Furthermore, we also found that the three tumor samples shared 64 SNVs which may be potential driver mutations. Twenty of those common 64 SNVs, located on 7 genes, are predicted to be damaging mutations by SIFT algorithm. These mutations are currently being validated using Sanger sequencing, and further RNA-seq in the same tumor samples to investigate for pathway disruption that may lead to chemo-refractory disease. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4833. doi:10.1158/1538-7445.AM2011-4833

Population sequencing of two endocannabinoid metabolic genes identifies rare and common regulatory variants associated with extreme obesity and metabolite level

BackgroundTargeted re-sequencing of candidate genes in individuals at the extremes of a quantitative phenotype distribution is a method of choice to gain information on the contribution of rare variants to disease susceptibility. The endocannabinoid system mediates signaling in the brain and peripheral tissues involved in the regulation of energy balance, is highly active in obese patients, and represents a strong candidate pathway to examine for genetic association with body mass index (BMI).ResultsWe sequenced two intervals (covering 188 kb) encoding the endocannabinoid metabolic enzymes fatty-acid amide hydrolase (FAAH) and monoglyceride lipase (MGLL) in 147 normal controls and 142 extremely obese cases. After applying quality filters, we called 1,393 high quality single nucleotide variants, 55% of which are rare, and 143 indels. Using single marker tests and collapsed marker tests, we identified four intervals associated with BMI: the FAAH promoter, the MGLL promoter, MGLL intron 2, and MGLL intron 3. Two of these intervals are composed of rare variants and the majority of the associated variants are located in promoter sequences or in predicted transcriptional enhancers, suggesting a regulatory role. The set of rare variants in the FAAH promoter associated with BMI is also associated with increased level of FAAH substrate anandamide, further implicating a functional role in obesity.ConclusionsOur study, which is one of the first reports of a sequence-based association study using next-generation sequencing of candidate genes, provides insights into study design and analysis approaches and demonstrates the importance of examining regulatory elements rather than exclusively focusing on exon sequences.