Geographic Distribution Of Mutations Research Articles

CARD9 mutations in patients with fungal infections: An update from the last 5 years.

Autosomal recessive deficiency in the caspase recruitment domain-containing protein 9 (CARD9) is a congenital immunological condition that leads to susceptibility to mucocutaneous and invasive fungal infections. There is growing incidence of fungal infections in patients with CARD9 deficiency, a phenomenon that is increasingly recognised. This study aimed to assess the frequency, geographic distribution and nature of mutations in patients with CARD9 deficiency, based on published papers in the literature until March 2023. We swiftly conducted a study to pinpoint every documented instance of fungal infections arising from CARD9 deficiency. We selected case reports from the databases of PubMed, Embase, Scopus and Google Scholar spanning the period from October 2009 to March 2023. We analysed 90 cases of fungal infections and identified 32 mutations in the CARD9 gene. Notably, the homozygous (HMZ) p.Q295X (c.883C > T) mutation was associated with an increased risk of candidiasis. In contrast, the HMZ p.Q289X (c.865C > T) mutation is linked to a higher risk of dermatophytosis. We observed differences in the geographical distribution of these mutations. The primary mutations found in African patients differ from those in Asian patients. Specifically, Asian patients exhibit a broader spectrum of CARD9 mutations than African patients. The diversity of mutations observed in the 90 cases revealed 32 distinct variations, emphasising the unique genetic alterations in the CARD9 gene associated with specific geographical areas and the corresponding prevalence of fungal infections.

Sequence Similarity Network Analysis Provides Insight into the Temporal and Geographical Distribution of Mutations in SARS-CoV-2 Spike Protein.

Severe acute respiratory syndrome-related coronavirus (SARS-CoV-2), which still infects hundreds of thousands of people globally each day despite various countermeasures, has been mutating rapidly. Mutations in the spike (S) protein seem to play a vital role in viral stability, transmission, and adaptability. Therefore, to control the spread of the virus, it is important to gain insight into the evolution and transmission of the S protein. This study deals with the temporal and geographical distribution of mutant S proteins from sequences gathered across the US over a period of 19 months in 2020 and 2021. The S protein sequences are studied using two approaches: (i) multiple sequence alignment is used to identify prominent mutations and highly mutable regions and (ii) sequence similarity networks are subsequently employed to gain further insight and study mutation profiles of concerning variants across the defined time periods and states. Additionally, we tracked the variants using visualizations on geographical maps. The visualizations produced using the Directed Weighted All Nearest Neighbors (DiWANN) networks and maps provided insights into the transmission of the virus that reflect well the statistics reported for the time periods studied. We found that the networks created using DiWANN are superior to commonly used approximate distance networks created using BLAST bitscores. The study offers a richer computational approach to analyze the transmission profile of the prominent S protein mutations in SARS-CoV-2 and can be extended to other proteins and viruses.

Analysis of β Globin Mutations in the Indian Population: Presence of Rare and Novel Mutations and Region Wise Heterogeneity.

β-thalassaemia is a major public health problem in India. A comprehensive data base of the spectrum of mutations causing β thalassaemia in the Indian population is necessary. Each population group in which the disease is prevalent has a different spectrum of β globin mutations and a few mutations account for most of the alleles. From 1997 to 2006, β-Globin gene mutation analysis was carried out in 1030 individuals. The common mutations in the population were screened by reverse dot blot (RDB). Deletion of 619 bp of the β globin gene was detected by gap-PCR. Rare mutations were screened using temporal temperature gel electrophoresis (TTGE) and DNA sequencing. Haplotyping of rare mutations was done by using established PCR-RFLP methods. Out of the 1030 individuals, 515 were homozygous or compound heterozygotes. Among the others, 178 had heterozygous β thalassaemia, 292 HbE-βthalassaemia, 27 HbS-β thalassaemia, 3 HPFH-β thalassaemia, 5 Lepore-β thalassaemia and 10 (δβ)0-β thalassaemia. Mutation analysis was performed on a total of 1545 β globin alleles from the subjects included in the study. The regional distribution of study subjects were: 533 from the South (Kerala, Tamilnadu, Andhra Pradesh and Karnataka), 529 from the East (Bihar, Orissa, West Bengal and other eastern states), 233 from the West (Gujarat, Maharashtra, Madhyapradesh and Rajasthan) and 92 from the Northern part of the country (Harayana, Punjab, Uttar Pradesh). A total of 41 mutations including 17 mutations that have not been reported earlier in this population were detected. Four, Codon 62/64 (−7bp), Codon 81/87 (−22bp), −25 (A→G) and IVS II- 613 (C→T) are novel mutations causing β thalassaemia. Thirteen mutations, which were detected in other populations but were not reported earlier in the Indian population, were identified. They included −29 (A→G), −87 (C→G), −90 (C→T), Codon 17 (A→T), Codon 22/23/24 (−17 bp), Codon 26 (G→T), Codon 36/37 (−T), Codon 41 (−C), IVS I-129 (A→C), IVS I-130 (G→C), IVS I-130 (G→A), Codon 106/107 (+G) and Codon 110 (T→C). Comparison of the spectrum of β thalassaemia mutations between different regions shows that there are considerable differences in the geographical distribution of mutations in the Indian population (Table). Haplotype analysis revealed that the rare mutations occured denovo and also through population migration. This data will aid in carrier detection, genetic counselling and prenatal diagnosis which play an important role in the prevention of the disease.Regional Distribution of β globin Mutations in India (%)MutationSouthEastNorthWestIVS I-5(G-C)57.4173.5154.3549.36CD 15(G-A)12.386.9903poly A (T-C)90.7300.86−28(A-G)4.5000IVS II-837 (T-G)2.81000CD 30(G-C)1.97.281.092.58CD 41/42(-TCTT)2.063.646.525.15619 bp DEL00.448.720.17IVS I-1(G-T)0.90.1511.9610.73CD 8/9 (+G)0.11.63.263OTHERS8.945.6714.135.15