scholarly journals MEN1 Mutations in Hürthle Cell (Oncocytic) Thyroid Carcinoma

2015 ◽  
Vol 100 (4) ◽  
pp. E611-E615 ◽  
Author(s):  
Katayoon Kasaian ◽  
Ana-Maria Chindris ◽  
Sam M. Wiseman ◽  
Karen L. Mungall ◽  
Thomas Zeng ◽  
...  
Keyword(s):  
Thyroid Carcinoma ◽  
Sequence Data ◽  
Whole Genome Sequence ◽  
Regulation Of Transcription ◽  
Whole Genome ◽  
Loss Of Function ◽  
Transcription Control ◽  
Thyroid Carcinomas ◽  
Normal Tissues ◽  
Hürthle Cell

Context and Objective: Oncocytic thyroid carcinoma, also known as Hürthle cell thyroid carcinoma, accounts for only a small percentage of all thyroid cancers. However, this malignancy often presents at an advanced stage and poses unique challenges to patients and clinicians. Surgical resection of the tumor accompanied in some cases by radioactive iodine treatment, radiation, and chemotherapy are the established modes of therapy. Knowledge of the perturbed oncogenic pathways can provide better understanding of the mechanism of disease and thus opportunities for more effective clinical management. Design and Patients: Initially, two oncocytic thyroid carcinomas and their matched normal tissues were profiled using whole genome sequencing. Subsequently, 72 oncocytic thyroid carcinomas, one cell line, and five Hürthle cell adenomas were examined by targeted sequencing for the presence of mutations in the multiple endocrine neoplasia I (MEN1) gene. Results: Here we report the identification of MEN1 loss-of-function mutations in 4% of patients diagnosed with oncocytic thyroid carcinoma. Whole genome sequence data also revealed large regions of copy number variation encompassing nearly the entire genomes of these tumors. Conclusion: Menin, a ubiquitously expressed nuclear protein, is a well-characterized tumor suppressor whose loss is the cause of MEN1 syndrome. Menin is involved in several major cellular pathways such as regulation of transcription, control of cell cycle, apoptosis, and DNA damage repair pathways. Mutations of this gene in a subset of Hürthle cell tumors point to a potential role for this protein and its associated pathways in thyroid tumorigenesis.

scholarly journals Soybean Haplotype Map (GmHapMap): A Universal Resource for Soybean Translational and Functional Genomics

2019 ◽  
Author(s):  
Davoud Torkamaneh ◽  
Jérôme Laroche ◽  
Babu Valliyodan ◽  
Louise O’Donoughue ◽  
Elroy Cober ◽  
...  
Keyword(s):  
Glycine Max ◽  
Gene Function ◽  
Oil Content ◽  
Seed Oil ◽  
Sequence Data ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Loss Of Function ◽  
Seed Oil Content ◽  
Extensive Coverage

AbstractHere we describe the first worldwide haplotype map for soybean (GmHapMap) constructed using whole-genome sequence data for 1,007 Glycine max accessions and yielding 15 million variants. The number of unique haplotypes plateaued within this collection (4.3 million tag SNPs) suggesting extensive coverage of diversity within the cultivated germplasm. We imputed GmHapMap variants onto 21,618 previously genotyped (50K array/210K GBS) accessions with up to 96% success for common alleles. A GWAS performed with imputed data enabled us to identify a causal SNP residing in the NPC1 gene and to demonstrate its role in controlling seed oil content. We identified 405,101 haplotypes for the 55,589 genes and show that such haplotypes can help define alleles. Finally, we predicted 18,031 putative loss-of-function (LOF) mutations in 10,662 genes and illustrate how such a resource can be used to explore gene function. The GmHapMap provides a unique worldwide resource for soybean genomics and breeding.

scholarly journals Characterising the loss-of-function impact of 5’ untranslated region variants in whole genome sequence data from 15,708 individuals

2019 ◽  
Author(s):  
Nicola Whiffin ◽  
Konrad J Karczewski ◽  
Xiaolei Zhang ◽  
Sonia Chothani ◽  
Miriam J Smith ◽  
...  
Keyword(s):  
Human Disease ◽  
Large Scale ◽  
Sequence Data ◽  
Case Reports ◽  
Protein Translation ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Loss Of Function ◽  
Genetic Sequencing ◽  
Strong Negative Selection

AbstractUpstream open reading frames (uORFs) are important tissue-specific cis-regulators of protein translation. Although isolated case reports have shown that variants that create or disrupt uORFs can cause disease, genetic sequencing approaches typically focus on protein-coding regions and ignore these variants. Here, we describe a systematic genome-wide study of variants that create and disrupt human uORFs, and explore their role in human disease using 15,708 whole genome sequences collected by the Genome Aggregation Database (gnomAD) project. We show that 14,897 variants that create new start codons upstream of the canonical coding sequence (CDS), and 2,406 variants disrupting the stop site of existing uORFs, are under strong negative selection. Furthermore, variants creating uORFs that overlap the CDS show signals of selection equivalent to coding loss-of-function variants, and uORF-perturbing variants are under strong selection when arising upstream of known disease genes and genes intolerant to loss-of-function variants. Finally, we identify specific genes where perturbation of uORFs is likely to represent an important disease mechanism, and report a novel uORF frameshift variant upstream of NF2 in families with neurofibromatosis. Our results highlight uORF-perturbing variants as an important and under-recognised functional class that can contribute to penetrant human disease, and demonstrate the power of large-scale population sequencing data to study the deleteriousness of specific classes of non-coding variants.

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.

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.

148 Multiple Dysregulated Novel Pathways and Genes in Aleutian Mink Disease Revealed by Selection Signatures and Gene Network Analyses Using Whole-genome Sequence Data

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 76-76
Author(s):  
Seyed Milad Vahedi ◽  
Karim Karimi ◽  
Siavash Salek Ardestani ◽  
Younes Miar
Keyword(s):  
Sequence Data ◽  
American Mink ◽  
Enrichment Analysis ◽  
Whole Genome Sequence ◽  
Fixation Index ◽  
Pathway Enrichment Analysis ◽  
Whole Genome ◽  
Nucleotide Polymorphisms ◽  
Network Analyses ◽  
Genome Level

Abstract Aleutian disease (AD) is a chronic persistent infection in domestic mink caused by Aleutian mink disease virus (AMDV). Female mink’s fertility and pelt quality depression are the main reasons for the AD’s negative economic impacts on the mink industry. A total number of 79 American mink from the Canadian Center for Fur Animal Research at Dalhousie University (Truro, NS, Canada) were classified based on the results of counter immunoelectrophoresis (CIEP) tests into two groups of positive (n = 48) and negative (n = 31). Whole-genome sequences comprising 4,176 scaffolds and 8,039,737 single nucleotide polymorphisms (SNPs) were used to trace the selection footprints for response to AMDV infection at the genome level. Window-based fixation index (Fst) and nucleotide diversity (θπ) statistics were estimated to compare positive and negative animals’ genomes. The overlapped top 1% genomic windows between two statistics were considered as potential regions underlying selection pressures. A total of 98 genomic regions harboring 33 candidate genes were detected as selective signals. Most of the identified genes were involved in the development and functions of immune system (PPP3CA, SMAP2, TNFRSF21, SKIL, and AKIRIN2), musculoskeletal system (COL9A2, PPP1R9A, ANK2, AKAP9, and STRIT1), nervous system (ASCL1, ZFP69B, SLC25A27, MCF2, and SLC7A14), reproductive system (CAMK2D, GJB7, SSMEM1, C6orf163), liver (PAH and DPYD), and lung (SLC35A1). Gene-expression network analysis showed the interactions among 27 identified genes. Moreover, pathway enrichment analysis of the constructed genes network revealed significant oxytocin (KEGG: hsa04921) and GnRH signaling (KEGG: hsa04912) pathways, which are likely to be impaired by AMDV leading to dams’ fecundity reduction. These results provided a perspective to the genetic architecture of response to AD in American mink and novel insight into the pathogenesis of AMDV.

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