Articles written in Journal of Genetics
Volume 88 Issue 2 August 2009 pp 227-232 Research Article
Volume 89 Issue 2 August 2010 pp 121-133 Research Article
Genetic relationships among 52
Volume 92 Issue 1 April 2013 pp 135-139 Research Note
Volume 98 All articles Published: 13 February 2019 Article ID 0008 RESEARCH ARTICLE
Insulin is a commonly used measure of pancreatic β-cell function but exhibits a short half-life in the human body. During biosynthesis, insulin release is accompanied by C-peptide at an equimolar concentration which has a much higher plasma half-life and is therefore projected as a precise measure of β-cell activity than insulin. Despite this, genetic studies of metabolic traits haveneglected the regulatory potential of C-peptide for therapeutic intervention of type-2 diabetes. The present study is aimed to search genomewide variants governing C-peptide levels in genetically diverse and high risk population for metabolic diseases—Indians. We performed whole genome genotyping in 877 healthy Indians of Indo-European origin followed by replication of variants with
Volume 98 All articles Published: 13 May 2019 Article ID 0050 RESEARCH ARTICLE
Panicle traits are the most important agronomic characters which directly relate to yield in rice. Panicle length (PL) being one of the major components of rice panicle structure is controlled by quantitative trait loci (QTLs). In our research, conducted at Research Farm of SKUAST-J, crosses of parental lines K343 and DHMAS were made for generating F2 mapping population, which were then transplanted into the field using augmented design-I. The F2 population was used for phenotypic evaluation, development of linkage map and identification of QTLs on the chromosomes by using SSR markers. A total of 450 SSR markers were used for screening both the parents of which 53 highly polymorphic markers were selected and used for genotyping of 233 genotypes of F2population. Linkage map was generated using MAPMAKER/EXP3.0 software, seven linkage groups were found distributed on 11 chromosomes of rice. QTLs were detected using QTL Cartographer (v2.5) software. Based on 1000 permutation tests, a logarithm of odds (LOD) threshold value 2.0 and 3.0 was set. Composite interval mapping was used to map QTLs in populations derived from bi-parental crosses. The phenotypic data, genotypic data and the genetic linkage map generated identified total three QTLs of which one was identified for PL qPL2, located at 85.01 cM position with 2.1 LOD value and in between the marker intervals RM324–RM208, this QTL explained the phenotype variation by 4.36%. The other two QTLs were identified for spikelet density (SD) qSD3.1 and qSD3.2, located at 28.91 and 39.51 cM, respectively, both with a flanking marker RM6832 on chromosome 3. The LOD value and phenotypic variation explained for qSD3.1 and qSD3.2 was 3.00 and 3.25; 9.70 and 12.34% respectively. The reported QTLs identified in the study suggested a less diversity in the parents used and also the rejection of not so useful markers from the used set of markers for PL and SD.
Volume 100 All articles Published: 31 May 2021 Article ID 0035 RESEARCH NOTE
Congenital deafness is one of the common disorders, with some common genes accounting for most of the cases. One in 1000 children are born with sensorineural hearing loss, and of that 50% are hereditary. In the Mediterranean Europeans, 80% of the nonsyndromic recessive deafness is due to homozygous mutation in GJB2, the 35del G allele. InWestern population, the GJB2 variation have been found in up to 30–40% cases. In Indians, the GJB2 variants have been found in up to 20% cases, mostly from central and southern India. Inthe present study, DNA was extracted from blood using standard methods. This was used to perform targeted gene capture using a custom capture kit. Multiple genes causing deafness were sequenced by next-generation sequencing to mean[80–100x coverage on Illumina sequencing platform. We found variants in GJB2, WFS1, FGF3, EYA4, MYO7A and CHD7 genes. Most of these variants were pathogenic and novel, and possibly causative. Deafness is most commonly due to the autosomal dominant genes but in severe cases of early onset deafness, autosomal recessive genes may contribute in our population. In selected families of severe prelingual deafness, prenatal diagnosis can be done.
Volume 101, 2022
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