Sequence variants from whole genome sequencing a large group of Icelanders

Abstract Background Impaired fertility in cattle limits the efficiency of livestock production systems. Unraveling the genetic architecture of fertility traits would facilitate their improvement by selection. In this study, we characterized SNP chip haplotypes at QTL blocks then used whole-genome sequencing to fine map genomic regions associated with reproduction in a population of Nellore (Bos indicus) heifers. Methods The dataset comprised of 1337 heifers genotyped using a GeneSeek® Genomic Profiler panel (74677 SNPs), representing the daughters from 78 sires. After performing marker quality control, 64800 SNPs were retained. Haplotypes carried by each sire at six previously identified QTL on BTAs 5, 14 and 18 for heifer pregnancy and BTAs 8, 11 and 22 for antral follicle count were constructed using findhap software. The significance of the contrasts between the effects of every two paternally-inherited haplotype alleles were used to identify sires that were heterozygous at each QTL. Whole-genome sequencing data localized to the haplotypes from six sires and 20 other ancestors were used to identify sequence variants that were concordant with the haplotype contrasts. Enrichment analyses were applied to these variants using KEGG and MeSH libraries. Results A total of six (BTA 5), six (BTA 14) and five (BTA 18) sires were heterozygous for heifer pregnancy QTL whereas six (BTA 8), fourteen (BTA 11), and five (BTA 22) sires were heterozygous for number of antral follicles’ QTL. Due to inadequate representation of many haplotype alleles in the sequenced animals, fine mapping analysis could only be reliably performed for the QTL on BTA 5 and 14, which had 641 and 3733 concordant candidate sequence variants, respectively. The KEGG “Circadian rhythm” and “Neurotrophin signaling pathway” were significantly associated with the genes in the QTL on BTA 5 whereas 32 MeSH terms were associated with the QTL on BTA 14. Among the concordant sequence variants, 0.2% and 0.3% were classified as missense variants for BTAs 5 and 14, respectively, highlighting the genes MTERF2, RTMB, ENSBTAG00000037306 (miRNA), ENSBTAG00000040351, PRKDC, and RGS20. The potential causal mutations found in the present study were associated with biological processes such as oocyte maturation, embryo development, placenta development and response to reproductive hormones. Conclusions The identification of heterozygous sires by positionally phasing SNP chip data and contrasting haplotype effects for previously detected QTL can be used for fine mapping to identify potential causal mutations and candidate genes. Genomic variants on genes MTERF2, RTBC, miRNA ENSBTAG00000037306, ENSBTAG00000040351, PRKDC, and RGS20, which are known to have influence on reproductive biological processes, were detected.

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Mining underutilized whole-genome sequencing projects to improve 16S rRNA databases

10.1101/2021.01.01.425045 ◽

2021 ◽

Author(s):

Ben Nolan ◽

Florence Abram ◽

Fiona Brennan ◽

Ashleigh Holmes ◽

Vincent O’Flaherty ◽

...

Keyword(s):

16S Rrna ◽

Whole Genome Sequencing ◽

16S Rdna ◽

Genome Sequencing ◽

Sequence Variants ◽

Whole Genome ◽

Short Reads ◽

A Genome ◽

Rrna Sequences ◽

16S Rrna Sequences

AbstractCurrent approaches to interpreting 16S rDNA amplicon data are hampered by several factors. Among these are database inaccuracy or incompleteness, sequencing error, and biased DNA/RNA extraction. Existing 16S rRNA databases source the majority of sequences from deposited amplicon sequences, draft genomes, and complete genomes. Most of the draft genomes available are assembled from short reads. However, repeated ribosomal regions are notoriously difficult to assemble well from short reads, and as a consequence the short-read-assembled 16S rDNA region may be an amalgamation of different loci within the genome. This complicates high-resolution community analysis, as a draft genome’s 16S rDNA sequence may be a chimera of multiple loci; in such cases, the draft-derived sequences in a database may not represent a 16S rRNA sequence as it occurs in biology. We present Focus16, a pipeline for improving 16S rRNA databases by mining NCBI’s Sequence Read Archive for whole-genome sequencing runs that could be reassembled to yield additional 16S rRNA sequences. Using riboSeed (a genome assembly tool for correcting rDNA misassembly), Focus16 provides a way to augment 16S rRNA databases with high-quality re-assembled sequences. In this study, we augmented the widely-used SILVA 16S rRNA database with the novel sequences disclosed by Focus16 and re-processed amplicon sequences from several benchmarking datasets with DADA2. Using this augmented SILVA database increased the number of amplicon sequence variants that could be assigned taxonomic annotations. Further, fine-scale classification was improved by revealing ambiguities. We observed, for example, that amplicon sequence variants (ASVs) may be assigned to a specific genus where Focus16-correction would indicate that the ASV is represented in two or more genera. Thus, we demonstrate that improvements can be made to taxonomic classification by incorporating these carefully re-assembled 16S rRNA sequences, and we invite the community to expand our work to augment existing 16S rRNA reference databases such as SILVA, GreenGenes, and RDP.

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Mechanisms of atrial fibrillation: genetics

ESC CardioMed ◽

10.1093/med/9780198784906.003.0497 ◽

2018 ◽

pp. 2120-2125

Author(s):

David O. Arnar ◽

Hilma Holm

Keyword(s):

Atrial Fibrillation ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Complex Traits ◽

Association Studies ◽

Sequence Variants ◽

Whole Genome ◽

Established Risk Factor ◽

Genome Wide ◽

Sequencing Studies

While atrial fibrillation (AF) is common and has serious consequences, a lot is yet unknown about the causative factors underlying this arrhythmia. The role of genetics in the development of AF has become more evident in the past decade. Family history is now a firmly established risk factor and many common and rare sequence variants linked to AF have been identified. Genome-wide association studies have identified common sequence variants that associate with AF, including variants on chromosomes 4q25, 16q22, and 1q22. Nevertheless, it has become apparent that despite these findings, a substantial fraction of heritability of most complex traits remained unaccounted for. This raises the possibility that development of AF is determined by the combination of common and rare susceptibility variants. Whole genome sequencing is the most comprehensive method to analyse individual genetic variation. A paradigm shift from microarray-based genotyping studies to whole exome and whole genome sequencing is ongoing. Whole genome sequencing studies have shown mutations in myosin genes may be associated with AF, implying that variants encoding sarcomere genes may be involved in the development of this arrhythmia. While some of the sequence variants discovered suggest novel mechanisms in the pathophysiology of this complex arrhythmia, much work is still needed to fully understand the mechanisms linking many of these loci to AF. Likewise, the current clinical applicability of this information is still unclear. However, further developments in this field are expected to add to our understanding of this complex arrhythmia and hopefully lead to new therapeutic possibilities.

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