scholarly journals Comrad: detection of expressed rearrangements by integrated analysis of RNA-Seq and low coverage genome sequence data

2011 ◽  
Vol 27 (11) ◽  
pp. 1481-1488 ◽  
Author(s):  
Andrew McPherson ◽  
Chunxiao Wu ◽  
Iman Hajirasouliha ◽  
Fereydoun Hormozdiari ◽  
Faraz Hach ◽  
...  
Keyword(s):  
Genome Sequence ◽  
Sequence Data ◽  
Integrated Analysis ◽  
Rna Seq ◽  
Genome Sequence Data ◽  
Low Coverage

scholarly journals An accurate assignment test for extremely low‐coverage whole‐genome sequence data

2021 ◽  
Author(s):  
Giada Ferrari ◽  
Lane M. Atmore ◽  
Sissel Jentoft ◽  
Kjetill S. Jakobsen ◽  
Daniel Makowiecki ◽  
...  
Keyword(s):  
Genome Sequence ◽  
Sequence Data ◽  
Assignment Test ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Genome Sequence Data ◽  
Low Coverage

scholarly journals An accurate assignment test for extremely low-coverage whole-genome sequence data

2021 ◽  
Author(s):  
Giada Ferrari ◽  
Lane M Atmore ◽  
Sissel Jentoft ◽  
Kjetill S Jakobsen ◽  
Daniel Makowiecki ◽  
...  
Keyword(s):  
Genome Sequence ◽  
Atlantic Cod ◽  
Sequence Data ◽  
Biological Characteristics ◽  
Assignment Test ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Genome Sequence Data ◽  
Assignment Tests ◽  
Low Coverage

Genomic assignment tests can provide important diagnostic biological characteristics, such as population of origin or ecotype. In ancient DNA research, such characters can provide further information on population continuity, evolution, climate change, species migration, or trade, depending on archaeological context. Yet, assignment tests often rely on moderate- to high-coverage sequence data, which can be difficult to obtain for many ancient specimens and in ecological studies, which often use sequencing techniques such as ddRAD to bypass the need for costly whole-genome sequencing. We have developed a novel approach that efficiently assigns biologically relevant information (such as population identity or structural variants) in extremely low-coverage sequence data. First, we generate databases from existing reference data using a subset of diagnostic Single Nucleotide Polymorphisms (SNPs) associated with a biological characteristic. Low coverage alignment files from ancient specimens are subsequently compared to these databases to ascertain allelic state yielding a joint probability for each association. To assess the efficacy of this approach, we assigned inversion haplotypes and population identity in several species including Heliconius butterflies, Atlantic herring, and Atlantic cod. We used both modern and ancient specimens, including the first whole-genome sequence data recovered from ancient herring bones. The method accurately assigns biological characteristics, including population membership, using extremely low-coverage (e.g. 0.0001x fold) based on genome-wide SNPs. This approach will therefore increase the number of ancient samples in ecological and bioarchaeological research for which relevant biological information can be obtained.

scholarly journals A novel variant in TAF1 affects gene expression and is associated with X-linked TAF1 intellectual disability syndrome

2018 ◽  
Vol 2 (3) ◽  
Author(s):  
Sarah E. Hurst ◽  
Erika Liktor-Busa ◽  
Aubin Moutal ◽  
Sara Parker ◽  
Sydney Rice ◽  
...  
Keyword(s):  
Cell Proliferation ◽  
Intellectual Disability ◽  
Genome Sequence ◽  
Sequence Data ◽  
Neuronal Cell ◽  
Global Developmental Delay ◽  
Whole Genome ◽  
Rna Seq ◽  
Genome Sequence Data ◽  
Novel Variant

We investigated the genome of a 5-year-old male who presented with global developmental delay (motor, cognitive, and speech), hypotonia, possibly ataxia, and cerebellar hypoplasia of unknown origin. Whole genome sequencing (WGS) and mRNA sequencing (RNA-seq) were performed on a family having an affected proband, his unaffected parents, and maternal grandfather. To explore the molecular and functional consequences of the variant, we performed cell proliferation assays, quantitative real-time PCR (qRT-PCR) array, immunoblotting, calcium imaging, and neurite outgrowth experiments in SH-SY5Y neuroblastoma cells to compare the properties of the wild-type TATA-box-binding protein factor 1 (TAF1), deletion of TAF1, and TAF1 variant p.Ser1600Gly samples. The whole genome data identified several gene variants. However, the genome sequence data failed to implicate a candidate gene as many of the variants were of unknown significance. By combining genome sequence data with transcriptomic data, a probable candidate variant, p.Ser1600Gly, emerged in TAF1. Moreover, the RNA-seq data revealed a 90:10 extremely skewed X-chromosome inactivation (XCI) in the mother. Our results showed that neuronal ion channel genes were differentially expressed between TAF1 deletion and TAF1 variant p.Ser1600Gly cells, when compared with their respective controls, and that the TAF1 variant may impair neuronal differentiation and cell proliferation. Taken together, our data suggest that this novel variant in TAF1 plays a key role in the development of a recently described X-linked syndrome, TAF1 intellectual disability syndrome, and further extends our knowledge of a potential link between TAF1 deficiency and defects in neuronal cell function.

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 Draft genome sequence data of the facultative, thermophilic, xylanolytic bacterium Paenibacillus sp. strain DA-C8

Data in Brief ◽  
2021 ◽  
Vol 35 ◽  
pp. 106784
Author(s):  
Chinda Chhe ◽  
Ayaka Uke ◽  
Sirilak Baramee ◽  
Umbhorn Ungkulpasvich ◽  
Chakrit Tachaapaikoon ◽  
...  
Keyword(s):  
Genome Sequence ◽  
Sequence Data ◽  
Draft Genome ◽  
Draft Genome Sequence ◽  
Genome Sequence Data ◽  
Paenibacillus Sp

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
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