scholarly journals Invariant Genes in Human Genomes

2019 ◽  
Author(s):  
Ankit Kumar Pathak ◽  
Ashwin Kumar Jainarayanan ◽  
Samir Kumar Brahmachari
Keyword(s):  
Functional Analysis ◽  
Human Genome ◽  
Exome Sequencing ◽  
Allele Frequency ◽  
Large Scale ◽  
Genetic Disorders ◽  
Developmental Processes ◽  
Human Genomes ◽  
Different Populations ◽  
Major Emphasis

ABSTRACTWith large-scale human genome and exome sequencing, a lot of focus has gone in studying variations present in genomes and their associations to various diseases. Since major emphasis has been put on their variations, less focus has been given to invariant genes in the population. Here we present 60,706 genomes from the ExAC database to identify population specific invariant genes. Out of 1,336 total genes drawn from various population specific invariant genes, 423 were identified to be mostly (allele frequency less than 0.001) invariant across different populations. 46 of these invariant genes showed absolute invariance in all populations. Most of these common invariant genes have homologs in primates, rodents and placental mammals while 8 of them were unique to human genome and 3 genes still had unknown functions. Surprisingly, a majority were found to be X-linked and around 50% of these genes were not expressed in any tissues. The functional analysis showed that the invariant genes are not only involved in fundamental functions like transcription and translation but also in various developmental processes. The variations in many of these invariant genes were found to be associated with cancer, developmental diseases and dominant genetic disorders.

scholarly journals A computational framework to analyze human genomes

2019 ◽  
Vol 35 (2) ◽  
pp. 105-118
Author(s):  
Vinh Le
Keyword(s):  
Human Genome ◽  
Large Scale ◽  
Variant Calling ◽  
Computational Framework ◽  
Variant Annotation ◽  
Genomic Technologies ◽  
Short Read Alignment ◽  
Human Genomes ◽  
Genome Analyses ◽  
Key Steps

The advent of genomic technologies has led to the current genomic era. Large-scale human genome projects have resulted in a huge amount of genomic data. Analyzing human genomes is a challenging task including a number of key steps from short read alignment, variant calling, and variant annotating. In this paper, the state-of-the-art computational methods and databases for each step will be analyzed to suggest a practical and efficient guideline for whole human genome analyses. This paper also discusses frameworks to combine variants from various genome analysis pipelines to obtain reliable variants. Finally, we will address advantages as well as discordances of widely-used variant annotation methods to evaluate the clinical significance of variants. The review will empower bioinformaticians to efficiently perform human genome analyses, and more importantly, help genetic consultants understand and properly interpret mutations for clinical purposes.

scholarly journals Genome-wide analysis of mobile element insertions in human genomes

2021 ◽  
Author(s):  
Yiwei Niu ◽  
Xueyi Teng ◽  
Yirong Shi ◽  
Yanyan Li ◽  
Yiheng Tang ◽  
...  
Keyword(s):  
Large Scale ◽  
Genetic Disorders ◽  
Mobile Element ◽  
Structural Variants ◽  
1000 Genomes ◽  
Major Class ◽  
Human Genomes ◽  
Genome Wide ◽  
Human Genetic Disorders

AbstractMobile element insertions (MEIs) are a major class of structural variants (SVs) and have been linked to many human genetic disorders, including hemophilia, neurofibromatosis, and various cancers. However, human MEI resources from large-scale genome sequencing are still lacking compared to those for SNPs and SVs. Here, we report a comprehensive map of 36,699 non-reference MEIs constructed from 5,675 genomes, comprising 2,998 Chinese samples (∼26.2X, NyuWa) and 2,677 samples from the 1000 Genomes Project (∼7.4X, 1KGP). We discovered that LINE-1 insertions were highly enriched at centromere regions, implying the role of chromosome context in retroelement insertion. After functional annotation, we estimated that MEIs are responsible for about 9.3% of all protein-truncating events per genome. Finally, we built a companion database named HMEID for public use. This resource represents the latest and largest genomewide study on MEIs and will have broad utility for exploration of human MEI findings.

Construction and Functional Analysis of the Recombinant Bacteriocins Weissellicin-MBF from Weissella confusa MBF8-1

2020 ◽  
Vol 22 (1) ◽  
pp. 115-122
Author(s):  
Amarila Malik ◽  
Elita Yuliantie ◽  
Nisa Yulianti Suprahman ◽  
Theresa Linardi ◽  
Angelina Wening Widiyanti ◽  
...  
Keyword(s):  
Functional Analysis ◽  
Large Scale ◽  
Micrococcus Luteus ◽  
Affinity Column ◽  
Gene Expressions ◽  
His Tag ◽  
Recombinant Peptides ◽  
Weak Activity ◽  
Potential Alternative ◽  
Weissella Confusa

Background: Bacteriocins (Bac1, Bac2, and Bac3) from Weissella confusa MBF8-1, weissellicin- MBF, have been reported as potential alternative substances as well as complements to the existing antibiotics against many antimicrobial-resistant pathogens. Previously, the genes encoded in the large plasmid, pWcMBF8-1, and the spermicidal activity of their synthetic peptides, originally discovered Indonesia, have been studied. Three synthetic bacteriocins peptides of this weissellicin-MBF have been reported for their potential activities, i.e. antibacterial and spermicidal. Objective: The aim of this study was to construct the recombinant Bacteriocin (r-Bac) genes, as well as to investigate the gene expressions and their functional analysis. Method: Here, the recombinant Bacteriocin (r-Bac) genes were constructed and the recombinant peptides (r-Bac1, r-Bac2, and r-Bac3) in B. subtilis DB403 cells were produced on a large scale. After purification, using the His-tag affinity column, their potential bioactivities were measured as well as their antibacterial minimum inhibitory concentrations against Leuconostoc mesenteroides and Micrococcus luteus, were determined. Results: Pure His-tag-recombinant Bac1, Bac2, and Bac3 were obtained and they could inhibit the growth of L. mesenteroides and M. luteus. Conclusion: The recombinant bacteriocin could be obtained although with weak activity in inhibiting gram-positive bacterial growth.

Frequency and characterization of mutations in genes in a large cohort of patients referred to MODY registry

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Emily Breidbart ◽  
Liyong Deng ◽  
Patricia Lanzano ◽  
Xiao Fan ◽  
Jiancheng Guo ◽  
...  
Keyword(s):  
Genetic Testing ◽  
Exome Sequencing ◽  
Large Scale ◽  
Age Of Onset ◽  
Family Members ◽  
Ethnically Diverse ◽  
Monogenic Diabetes ◽  
Diabetes Diagnosis ◽  
Pathogenic Variants ◽  
Atypical Diabetes

Abstract Objectives There have been few large-scale studies utilizing exome sequencing for genetically undiagnosed maturity onset diabetes of the young (MODY), a monogenic form of diabetes that is under-recognized. We describe a cohort of 160 individuals with suspected monogenic diabetes who were genetically assessed for mutations in genes known to cause MODY. Methods We used a tiered testing approach focusing initially on GCK and HNF1A and then expanding to exome sequencing for those individuals without identified mutations in GCK or HNF1A. The average age of onset of hyperglycemia or diabetes diagnosis was 19 years (median 14 years) with an average HbA1C of 7.1%. Results Sixty (37.5%) probands had heterozygous likely pathogenic/pathogenic variants in one of the MODY genes, 90% of which were in GCK or HNF1A. Less frequently, mutations were identified in PDX1, HNF4A, HNF1B, and KCNJ11. For those probands with available family members, 100% of the variants segregated with diabetes in the family. Cascade genetic testing in families identified 75 additional family members with a familial MODY mutation. Conclusions Our study is one of the largest and most ethnically diverse studies using exome sequencing to assess MODY genes. Tiered testing is an effective strategy to genetically diagnose atypical diabetes, and familial cascade genetic testing identified on average one additional family member with monogenic diabetes for each mutation identified in a proband.

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