scholarly journals Transcriptional profile of platelets and iPSC-derived megakaryocytes from whole genome and RNA sequencing

Blood ◽  
2020 ◽  
Author(s):  
Kai Kammers ◽  
Margaret Taub ◽  
Benjamin Rodriguez ◽  
Lisa R Yanek ◽  
Ingo Ruczinski ◽  
...  
Keyword(s):  
Sequence Data ◽  
Blood Platelets ◽  
Induced Pluripotent Stem Cell ◽  
Normal Subjects ◽  
Blood Platelet ◽  
Tissue Expression ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Induced Pluripotent ◽  
Genomic Regions

GWAS studies have identified common variants associated with platelet related phenotypes, but because these variants are largely intronic or intergenic, their link to platelet biology is unclear. In 290 normal subjects from the GeneSTAR Research Study (110 African Americans (AAs) and 180 European Americans (EAs)), we generated whole genome sequence data from whole blood and RNA sequence (RNA-seq) data from extracted non-ribosomal RNA from 185 induced pluripotent stem cell-derived megakaryocyte (MK) cell lines (platelet precursor cells) and 290 blood platelet samples from these subjects. Using eigenMT software to select the peak SNP for each expressed gene, and meta-analyzing the results of AAs and EAs, we identify (q-value < 0.05) N=946 cis-expression quantitative trait loci (eQTLs) in derived MKs and N=1,830 cis-eQTLs in blood platelets. Among the 57 eQTLs shared between the two tissues the estimated directions of effect are very consistent (98.2% concordance). A high proportion of detected cis-eQTLs (74.9% in MKs and 84.3% in platelets) are unique to MKs and platelets compared to peak associated SNP-expressed gene pairs of 48 other tissue types that are reported in version V7 of the Genotype-Tissue Expression (GTEx) Project. The locations of our identified eQTLs are significantly enriched for overlap with several annotation tracks highlighting genomic regions with specific functionality in MKs, including MK-specific DNAse hotspots, H3K27-acetylation marks, H3K4-methylation marks, enhancers and super-enhancers. These results offer insights into the regulatory signature of MKs and platelets, with significant overlap in genes expressed, eQTLs detected, and enrichment within known super enhancers relevant to platelet biology.

46 Footprints of Selection in Angus and Hanwoo Beef Cattle Using Imputed Whole Genome Sequence Data

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 25-25
Author(s):  
Muhammad Yasir Nawaz ◽  
Rodrigo Pelicioni Savegnago ◽  
Cedric Gondro
Keyword(s):  
Beef Cattle ◽  
Genome Sequence ◽  
Sequence Data ◽  
Whole Genome Sequence ◽  
Fixation Index ◽  
Whole Genome ◽  
Extended Haplotype Homozygosity ◽  
Extended Haplotype ◽  
Genome Sequence Data ◽  
Genomic Regions

Abstract In this study, we detected genome wide footprints of selection in Hanwoo and Angus beef cattle using different allele frequency and haplotype-based methods based on imputed whole genome sequence data. Our dataset included 13,202 Angus and 10,437 Hanwoo animals with 10,057,633 and 13,241,550 imputed SNPs, respectively. A subset of data with 6,873,624 common SNPs between the two populations was used to estimate signatures of selection parameters, both within (runs of homozygosity and extended haplotype homozygosity) and between (allele fixation index, extended haplotype homozygosity) the breeds in order to infer evidence of selection. We observed that correlations between various measures of selection ranged between 0.01 to 0.42. Assuming these parameters were complementary to each other, we combined them into a composite selection signal to identify regions under selection in both beef breeds. The composite signal was based on the average of fractional ranks of individual selection measures for every SNP. We identified some selection signatures that were common between the breeds while others were independent. We also observed that more genomic regions were selected in Angus as compared to Hanwoo. Candidate genes within significant genomic regions may help explain mechanisms of adaptation, domestication history and loci for important traits in Angus and Hanwoo cattle. In the future, we will use the top SNPs under selection for genomic prediction of carcass traits in both breeds.

scholarly journals Genome-scale profiling reveals higher proportions of phylogenetic signal in non-coding data

2019 ◽  
Author(s):  
Robert Literman ◽  
Rachel S. Schwartz
Keyword(s):  
Genome Sequence ◽  
Sequence Data ◽  
Phylogenetic Signal ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Phylogenetic Information ◽  
Genome Sequence Data ◽  
Evolutionary Forces ◽  
Limited Degree ◽  
Genomic Regions

AbstractAccurate estimates of species relationships are integral to our understanding of evolution, yet many relationships remain controversial despite whole-genome sequence data. These controversies are due in part to complex patterns of phylogenetic and non-phylogenetic signal coming from regions of the genome experiencing distinct evolutionary forces, which can be difficult to disentangle. Here we profile the amounts and proportions of phylogenetic and non-phylogenetic signal derived from loci spread across mammalian genomes. We identified orthologous sequences from primates, rodents, and pecora, annotated sites as one or more of nine locus types (e.g. coding, intronic, intergenic), and profiled the phylogenetic information contained within locus types across evolutionary timescales associated with each clade. In all cases, non-coding loci provided more overall signal and a higher proportion of phylogenetic signal compared to coding loci. This suggests potential benefits of shifting away from primarily targeting genes or coding regions for phylogenetic studies, particularly in this era of accessible whole genome sequence data. In contrast to long-held assumptions about the phylogenetic utility of more variable genomic regions, most locus types provided relatively consistent phylogenetic information across timescales, although we find evidence that coding and intronic regions may, respectively and to a limited degree, inform disproportionately about older and younger splits. As part of this work we also validate the SISRS pipeline as an annotation-free ortholog discovery pipeline capable of identifying millions of phylogenetically informative sites directly from raw sequencing reads.

TIGER: inferring DNA replication timing from whole-genome sequence data

2021 ◽  
Author(s):  
Amnon Koren ◽  
Dashiell J Massey ◽  
Alexa N Bracci
Keyword(s):  
Dna Replication ◽  
Genome Sequence ◽  
Genomic Dna ◽  
Sequence Data ◽  
Replication Timing ◽  
Whole Genome Sequence ◽  
Supplementary Information ◽  
Whole Genome ◽  
Genome Sequence Data ◽  
Dna Replication Timing

Abstract Motivation Genomic DNA replicates according to a reproducible spatiotemporal program, with some loci replicating early in S phase while others replicate late. Despite being a central cellular process, DNA replication timing studies have been limited in scale due to technical challenges. Results We present TIGER (Timing Inferred from Genome Replication), a computational approach for extracting DNA replication timing information from whole genome sequence data obtained from proliferating cell samples. The presence of replicating cells in a biological specimen leads to non-uniform representation of genomic DNA that depends on the timing of replication of different genomic loci. Replication dynamics can hence be observed in genome sequence data by analyzing DNA copy number along chromosomes while accounting for other sources of sequence coverage variation. TIGER is applicable to any species with a contiguous genome assembly and rivals the quality of experimental measurements of DNA replication timing. It provides a straightforward approach for measuring replication timing and can readily be applied at scale. Availability and Implementation TIGER is available at https://github.com/TheKorenLab/TIGER. Supplementary information Supplementary data are available at Bioinformatics online

scholarly journals Whole genome sequence data of Mycobacterium tuberculosis XDR strain, isolated from patient in Kazakhstan

Data in Brief ◽  
2020 ◽  
Vol 33 ◽  
pp. 106416
Author(s):  
Asset Daniyarov ◽  
Askhat Molkenov ◽  
Saule Rakhimova ◽  
Ainur Akhmetova ◽  
Zhannur Nurkina ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Genome Sequence ◽  
Sequence Data ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Genome Sequence Data

scholarly journals Elucidating the genetic basis of an oligogenic birth defect using whole genome sequence data in a non-model organism, Bubalus bubalis

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Lynsey K. Whitacre ◽  
Jesse L. Hoff ◽  
Robert D. Schnabel ◽  
Sara Albarella ◽  
Francesca Ciotola ◽  
...  
Keyword(s):  
Genome Sequence ◽  
Birth Defect ◽  
Genetic Basis ◽  
Sequence Data ◽  
Model Organism ◽  
Bubalus Bubalis ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Genome Sequence Data

scholarly journals Whole genome characterization of strains belonging to the Ralstonia solanacearum species complex and in silico analysis of TaqMan assays for detection in this heterogenous species complex

2021 ◽  
Author(s):  
Viola Kurm ◽  
Ilse Houwers ◽  
Claudia E. Coipan ◽  
Peter Bonants ◽  
Cees Waalwijk ◽  
...  
Keyword(s):  
Ralstonia Solanacearum ◽  
In Silico ◽  
Species Complex ◽  
Sequence Data ◽  
In Silico Analysis ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Genome Sequences ◽  
Pcr Assays

AbstractIdentification and classification of members of the Ralstonia solanacearum species complex (RSSC) is challenging due to the heterogeneity of this complex. Whole genome sequence data of 225 strains were used to classify strains based on average nucleotide identity (ANI) and multilocus sequence analysis (MLSA). Based on the ANI score (>95%), 191 out of 192(99.5%) RSSC strains could be grouped into the three species R. solanacearum, R. pseudosolanacearum, and R. syzygii, and into the four phylotypes within the RSSC (I,II, III, and IV). R. solanacearum phylotype II could be split in two groups (IIA and IIB), from which IIB clustered in three subgroups (IIBa, IIBb and IIBc). This division by ANI was in accordance with MLSA. The IIB subgroups found by ANI and MLSA also differed in the number of SNPs in the primer and probe sites of various assays. An in-silico analysis of eight TaqMan and 11 conventional PCR assays was performed using the whole genome sequences. Based on this analysis several cases of potential false positives or false negatives can be expected upon the use of these assays for their intended target organisms. Two TaqMan assays and two PCR assays targeting the 16S rDNA sequence should be able to detect all phylotypes of the RSSC. We conclude that the increasing availability of whole genome sequences is not only useful for classification of strains, but also shows potential for selection and evaluation of clade specific nucleic acid-based amplification methods within the RSSC.

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