Genetics and exercise: an introduction
Adam P. Sharples, James P. Morton, Henning Wackerhage in Molecular Exercise Physiology, 2022
Chromosomes have two arms and a central constriction which is termed the centromere. The short arm of a chromosome is denoted as p and the long arm as q. Each arm of the chromosome is subdivided into regions numbered consecutively from the centromere to the telomere which is the tip of each chromosome arm. Each band (i.e. the dark and light stripes of a chromosome seen in Figure 3.5) within a given region is identified by a number. With this nomenclature, it is possible to specify any chromosomal region by its “cytological address”. For example, chromosome 1 is composed of about 249 million (mega, M) DNA base pairs (Figure 3.6). 1p22 refers to chromosome 1, p arm, region 2, band 2. Since the sequence of the DNA bases of the entire human genome is now available, it is possible to specify a physical position on a given human chromosome in terms of the exact base number in a sequence ranging from one to millions. For instance, there are 4,300 genes encoded on chromosome 1. The gene KIF1B which encodes kinesin family member 1B codes for a motor protein that transports vesicles within cells. It is located on 1p36.22 and extends from 10.21 to 10.38 M bases of DNA.
Plasma Cell Neoplasms
Wojciech Gorczyca in Atlas of Differential Diagnosis in Neoplastic Hematopathology, 2014
Patients with newly diagnosed myeloma with amp(1q21) had inferior 5-year event-free and overall survival compared with those lacking amp(1q21), and in a multivariate analysis, amp(1q21) was an independent poor prognostic factor [44]. In a microarray analysis of 532 newly diagnosed patients with myeloma reported by Shaughnessy et al. [107], 70 genes were linked to early disease-related death, many of them located on chromosome 1: ~50% of 19 underexpressed genes and 30% of 51 overexpressed genes were derived from chromosomes 1p and 1q, respectively. The molecular data suggest that alterations in the chromosome 1 may play a role in disease evolution by providing a growth and/or survival advantage [95,107]. Two recent series have failed to confirm the overriding negative prognostic association with chromosome 1 amplification detected by FISH [2,108].
In Vitro Cellular Aging and Immortalization
George E. Milo, Bruce C. Casto, Charles F. Shuler in Transformation of Human Epithelial Cells: Molecular and Oncogenetic Mechanisms, 2017
Ning et al.22 further showed that introduction of a normal human chromosome 4 into cell lines assigned to complementation group B restored the phenotype of limited proliferative potential. However, when the human chromosome 4 was introduced into cell lines assigning to the other complementation groups (A, C, and D), there was no decrease in proliferation potential and the phenotype of immortality was retained. Thus, it seems clear that genes on chromosome 4 code for some part of the genetic program that limits the division potential of normal cells in culture. Disruption of these genes leads to cells with an immortal phenotype. Sugawara et al.23 found a similar result in studies in which they introduced the normal human chromosome 1 into Chinese hamster cells. Human chromosome 1 was able to restore the cellular aging phenotype in these immortal hamster cells. It remains to be seen whether chromosome 1 plays a role in the immortalization of human cells.
Association between Fetal MTHFR A1298C (rs1801131) Polymorphism and Neural Tube Defects Risk: A Systematic Review and Meta-Analysis
Published in Fetal and Pediatric Pathology, 2022
Sara Soleimani-Jadidi, Bahare Meibodi, Atiyeh Javaheri, Razieh Sadat Tabatabaei, Amaneh Hadadan, Leila Zanbagh, Hajar Abbasi, Reza Bahrami, Seyed Reza Mirjalili, Mojgan Karimi-Zarchi, Hossein Neamatzadeh
The enzyme 5,10-methylenetetrahydrofolate reductase (MTHFR) plays an important role in the folate metabolism pathway and regulates the intracellular folate pool for synthesis and methylation of DNA folate metabolism [15]. Among genetic factors, variations in MTHFR gene have been assessed as potential risk factors in development of NTDs. The best-characterized MTHFR genetic mutation 677 C > T is associated with a 2-4 fold increased risk of NTDs if the patient is homozygous for this mutation [16]. It is suggested that folate transport may be affected by immunological responses and maternal autoantibodies that bind to the folate receptor, blocking the intracellular uptake of folate, which may then lead to NTDs [17]. The human gene has been mapped to the telomeric region of the chromosome 1 (1p36.3), consists of 11 exons, and spans a 2 kbp coding region [18–20]. The MTHFR A1298C polymorphism is an A to C transition at base pair 1298, occurs in exon 7 resulting in the Glu to valine substitution at position 429 of the protein at the C- terminal regulatory domain of the protein and decreases the enzyme activity [21, 22]. There have been several reports attempting to prove the association between MTHFR A1298C polymorphism and NTDs among different populations, but the results are controversial. Given that the results of previous studies remain inconclusive and controversial, we conducted the current meta-analysis to further evaluate the correlation between MTHFR A1298C (rs1801131) and the susceptibility to NTDs.
Testing differentially methylated regions through functional principal component analysis
Published in Journal of Applied Statistics, 2022
Mohamed Milad, Gayla R. Olbricht
To mimic methylation profile changes accurately, a simulation was constructed from the RRBS data set described above following the same approach as in M3D [13]. The regions (CpG clusters) were defined as follows: (1) CpG sites that covered at least 75% of samples were defined as frequently covered CpG sites and (2) a maximum distance of 100 base pairs to the nearest neighbor within a region was accepted. Using these criteria, only regions with at least 20 frequently covered CpG sites were used in the analysis [9]. The simulation study focused on the first 1000 regions on chromosome 1. Out of the 12 control samples in the RRBS data, 4 patients were randomly selected to use in the simulation study as controls. Four more replicates were simulated 100 times to be the testing group (i.e. cases). Of these, 250, 100 and 50 of the CpG clusters (predefined regions) were randomly selected to apply differential methylation changes. The replicates that acted as the testing group (cases) were simulated by first adding or subtracting random Poisson (λ =1) noise to the total number of reads at each cytosine. Uniform [−0.1, 0.1] random noise was added to cytosine methylation levels. The methylation level 13]. The degree of methylation level change was controlled by the parameter 13].
Discriminant Analysis of Lung Cancer Using Nonlinear Clustering of Copy Numbers
Published in Cancer Investigation, 2020
Nezamoddin N. Kachouie, Meshal Shutaywi, David C. Christiani
The cancer cluster obtained using copy numbers of chromosome 1 contains 71 samples, 44 of which are true cancer samples and 27 of them are normal samples falsely clustered in the cancer group. The remaining 55 samples (126–71 = 55) are grouped in the normal cluster, consisting of 36 non-involved samples (true negatives) and 19 cancer samples (false negatives). Top left panel of Figure 1 shows true cancer (black dots) and normal (red dots) groups for chromosome 1. Clustering result obtained by kernel K-means using copy numbers of chromosome 1 is depicted in Top right panel of Figure 1. For visualization purposes, X-Y axis in Figure 1 are first and second principal components obtained for the feature matrix of chromosome 1. The accuracy (true rate) and corresponding NMI computed for chromosome 1 are 63% and 0.0544, respectively.
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