Performance of methods to detect genetic variants from bisulphite sequencing data in a non-model species

BISCUIT: an efficient, standards-compliant tool suite for simultaneous genetic and epigenetic inference in bulk and single-cell studies

Data from both bulk and single-cell whole-genome DNA methylation experiments are under-utilized in many ways. This is attributable to inefficient mapping of methylation sequencing reads, routinely discarded genetic information, and neglected read-level epigenetic and genetic linkage information. We introduce the BISulfite-seq Command line User Interface Toolkit (BISCUIT) and its companion R/Bioconductor package, biscuiteer, for simultaneous extraction of genetic and epigenetic information from bulk and single-cell DNA methylation sequencing. BISCUIT's performance, flexibility and standards-compliant output allow large, complex experimental designs to be characterized on clinical timescales. BISCUIT is particularly suited for processing data from single-cell DNA methylation assays, with its excellent scalability, efficiency, and ability to greatly enhance mappability, a key challenge for single-cell studies. We also introduce the epiBED format for single-molecule analysis of coupled epigenetic and genetic information, facilitating the study of cellular and tissue heterogeneity from DNA methylation sequencing.

An ecologist's guide for studying DNA methylation variation in wild vertebrates

The field of molecular biology is advancing fast with new powerful technologies, sequencing methods and analysis software being developed constantly. Commonly used tools originally developed for research on humans and model species are now regularly used in ecological and evolutionary research. There is also a growing interest in the causes and consequences of epigenetic variation in natural populations. Studying ecological epigenetics is currently challenging, especially for vertebrate systems, because of the required technical expertise, complications with analyses and interpretation, and limitations in acquiring sufficiently high sample sizes. Importantly, neglecting the limitations of the experimental setup, technology and analyses may affect the reliability and reproducibility, and the extent to which unbiased conclusions can be drawn from these studies. Here, we provide a practical guide for researchers aiming to study DNA methylation variation in wild vertebrates. We review the technical aspects of epigenetic research, concentrating on DNA methylation using bisulfite sequencing, discuss the limitations and possible pitfalls, and how to overcome them through rigid and reproducible data analysis. This review provides a solid foundation for the proper design of epigenetic studies, a clear roadmap on the best practices for correct data analysis and a realistic view on the limitations for studying ecological epigenetics in vertebrates. This review will help researchers studying the ecological and evolutionary implications of epigenetic variation in wild populations.

A pipeline for sample tagging of whole genome bisulfite sequencing data using genotypes of whole genome sequencing

BACKGROUND

In large-scale high-throughput sequencing projects and biobank construction, sample tagging is essential to prevent sample mix-ups. Despite the availability of fingerprint panels for DNA data, little research has been conducted on sample tagging of whole genome bisulfite sequencing (WGBS) data. This study aims to construct a pipeline and identify applicable fingerprint panels to address this problem.

RESULTS

Using autosome-wide A/T polymorphic single nucleotide variants (SNVs) obtained from whole genome sequencing (WGS) and WGBS of individuals from the Third China National Stroke Registry, we designed a fingerprint panel and constructed an optimized pipeline for tagging WGBS data. This pipeline used Bis-SNP to call genotypes from the WGBS data, and optimized genotype comparison by eliminating wildtype homozygous and missing genotypes, and retaining variants with identical genomic coordinates and reference/alternative alleles. WGS-based and WGBS-based genotypes called from identical or different samples were extensively compared using hap.py. In the first batch of 94 samples, the genotype consistency rates were between 71.01%-84.23% and 51.43%-60.50% for the matched and mismatched WGS and WGBS data using the autosome-wide A/T polymorphic SNV panel. This capability to tag WGBS data was validated among the second batch of 240 samples, with genotype consistency rates ranging from 70.61%-84.65% to 49.58%-61.42% for the matched and mismatched data, respectively. We also determined that the number of genetic variants required to correctly tag WGBS data was on the order of thousands through testing six fingerprint panels with different orders for the number of variants. Additionally, we affirmed this result with two self-designed panels of 1351 and 1278 SNVs, respectively. Furthermore, this study confirmed that using the number of genetic variants with identical coordinates and ref/alt alleles, or identical genotypes could not correctly tag WGBS data.

CONCLUSION

This study proposed an optimized pipeline, applicable fingerprint panels, and a lower boundary for the number of fingerprint genetic variants needed for correct sample tagging of WGBS data, which are valuable for tagging WGBS data and integrating multi-omics data for biobanks.

Performance comparisons of methylation and structural variants from low-input whole-genome methylation sequencing

Aim: Whole-genome methylation sequencing carries both DNA methylation and structural variant information (single nucleotide variant [SNV]; copy number variant [CNV]); however, limited data is available on the reliability of obtaining this information simultaneously from low-input DNA using various library preparation and sequencing protocols. Methods: A HapMap NA12878 sample was sequenced with three protocols (EM-sequencing, QIA-sequencing and Swift-sequencing) and their performance was compared on CpG methylation measurement and SNV and CNV detection. Results: At low DNA input (10-25 ng), EM-sequencing was superior in almost all metrics except CNV detection where all protocols were similar. EM-sequencing captured the highest number of CpGs and true SNVs. Conclusion: EM-sequencing is suitable to detect methylation, SNVs and CNVs from single sequencing with low-input DNA.

Bioprospecting uncultivable microbial diversity in tannery effluent contaminated soil using shotgun sequencing and bio-reduction of chromium by indigenous chromate reductase genes

The tannery industry generates a consequential threat to the environment by producing a large amount of potentially toxic metal-containing waste. Bioremediation has been a promising approach for treating potentially toxic metals, but the efficiency of remediation in microbes is one of the factors limiting their application in tanneries waste treatment. The motivation behind the present work was to explore the microbial diversity and chromate reductase genes present in the tannery effluent-contaminated soil using metagenomics approach. The use of shotgun sequencing enabled the identification of operational parameters that influence microbiome composition and their ability to reduce Chromium (Cr) concentration. The Cr concentration in Kanpur tannery effluent contaminated soil sample was 700 ppm which is many folds than the approved permissible limit by World Health Organisation (WHO) for Cr is 100 ppm. Metagenomic Deoxyribo Nucleic Acid (DNA) was extracted to explore taxonomic community structure, phylogenetic linkages, and functional profile. With a Guanine-Cytosine (GC) abundance of 54%, total of 45,163,604 high-quality filtered reads were obtained. Bacteria (83%), Archaebacteria (14%), and Viruses (3%) were discovered in the structural biodiversity. Bacteria were classified to phylum level, with Proteobacteria (52%) being the dominant population, followed by Bacteriodetes (15%), Chloroflexi (15%), Spirochaetes (7%), Thermotogae (5%), Actinobacteria (4%), and Firmicutes (1%). The OXR genes were cloned and checked for their efficiency to reduce Cr concentration. Insitu validation of OXR8 gene showed a reduction of Cr concentration from 700 ppm to 24 ppm in 72 h (96.51% reduction). The results of this study suggests that there is a huge reservoir of microbes and chromate reductase genes which are unexplored yet.

Signatures of polygenic adaptation align with genome-wide methylation patterns in wild strawberry plants

Epigenetic inheritance can drive adaptive evolution independently of DNA sequence variation. However, to what extent epigenetic variation represents an autonomous evolutionary force remains largely elusive. Through gene ontology and comparative analyses of genomic and epigenomic variation of wild strawberry plants raised in distinct drought settings, we characterised genome-wide covariation between single nucleotide polymorphisms (SNPs) and differentially methylated cytosines (DMCs). Covariation between SNPs and DMCs was independent of genomic proximity, but instead associated with fitness-related processes such as stress responses, genome regulation and reproduction. We expected this functional SNP-DMC covariation to be driven by adaptive evolution canalising SNP and DMC variation, but instead observed significantly lower covariation with DMCs for adaptive rather than for neutral SNPs. Drought-induced DMCs frequently co-varied with tens of SNPs, suggesting high genomic redundancy as a broad potential basis for polygenic adaptation of gene expression. Our findings suggest that stress-responsive DMCs initially co-vary with many SNPs under increased environmental stress, and that natural selection acting upon several of these SNPs subsequently reduces standing covariation with stress-responsive DMCs. Our study supports DNA methylation profiles that represent complex quantitative traits rather than autonomous evolutionary forces. We provide a conceptual framework for polygenic regulation and adaptation shaping genome-wide methylation patterns in plants.