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Research Article
Y-Chromosome Microdeletion Screening in Senegalese Infertile Men
Adji Dieynaba Diallo*,
Arame Ndiaye,
Fatou Diop Gueye,
Ndiaga Diop,
Rokhaya Ndiaye,
Amath Thiam,
Abdoulaye Sega Diallo,
Mame Venus Gueye,
Mama Sy Diallo,
Oumar Faye
Issue:
Volume 11, Issue 4, December 2023
Pages:
112-118
Received:
21 September 2023
Accepted:
20 October 2023
Published:
30 November 2023
Abstract: Background: Significant progress has been made in recent years towards understanding the pathogenesis of spermatogenic arrest and infertility. Genetic factors contribute to 10-15% of male infertility. After chromosomal abnormalities, Azoospermia factor (AZF) microdeletions in the Yq region are the second most prevalent spermatogenic disorder among infertile men. Our study aimed to assess rates of chromosomal abnormalities and AZF microdeletions in Senegalese men diagnosed with azoospermia and oligozoospermia. Methods: Twenty-three men with azoospermia and oligozoospermia were chosen for molecular studies. Blood samples were analyzed for karyotyping and identification of Y chromosome microdeletions. Multiplex polymerase chain reaction was used to identify the complete deletion of AZF using six Sequence-Tagged Sites (STSs) (sY84 and sY86 in the AZFa region, sY127 and sY134 in the AZFb region, and sY254 and sY255 in the AZFc region). Results: During karyotyping analysis, it was observed that no chromosomal abnormalities were present except for four patients who had Klinefelter syndrome (XXY or XY/XXY; XX/XXY mosaics). Furthermore, AZF microdeletions were detected, with the most common being in the AZFc region, followed by AZFa and AZFb. Ten patients (62.5%, 10/16) exhibited deletion of AZFc markers sY254 and sY255. Of these, two patients (20%, 2/10) had sY254 deletion, one patient (10%, 1/10) had sY255 deletion, and seven patients (70%, 7/10) had sY254 + sY255 deletion which was significantly related to azoospermic phenotype (80%, 8/10). Additionally, four patients (25%, 4/16) had deletion of AZFa at marker sY86 and this was linked to both azoospermic and oligozoospermic. Finally, two patients (12.5%, 2/1) exhibited deletion AZFb in marker sY127, which was associated solely with azoospermia. However, microdeletions of the Y chromosome were detected in four azoospermic patients with abnormal karyotype. Conclusions: Our study indicates the presence of abnormal chromosome and Y chromosome microdeletions in the infertile Senegalese men, suggesting that screening for these should be part of their diagnostic.
Abstract: Background: Significant progress has been made in recent years towards understanding the pathogenesis of spermatogenic arrest and infertility. Genetic factors contribute to 10-15% of male infertility. After chromosomal abnormalities, Azoospermia factor (AZF) microdeletions in the Yq region are the second most prevalent spermatogenic disorder among ...
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Research Article
Genetic Variability in Sesame (Sesamum indicum L.) Genotypes for Shattering and Shattering-Related Traits
Issue:
Volume 11, Issue 4, December 2023
Pages:
119-125
Received:
25 September 2023
Accepted:
24 October 2023
Published:
30 November 2023
Abstract: Shattering has a substantial yield reduction in sesame. Sixty-four sesame genotypes were evaluated using 8 x 8 lattice design with two replications at the main research station of Pawe Agricultural Research Center to assess the genetic variability among sesame genotypes for shattering and shattering-related traits. Data were collected on days to first capsule opening, days to 90% maturity, number of opened-capsules plant-1, number of total capsules plant-1, length of cracking on opened-capsule, number of seeds dropped opened-capsule-1, number of seeds dropped opened-capsule-1 while the capsule is inverted, and the number of seeds retained opened-capsule-1. In the present study, the mean seed retention and rate of shattering capsule-1 ranged from 22.56% to 73.71% and from 26.20% to 77.78%, respectively. Analysis of variance revealed significance difference (P<0.05) among sesame genotypes for number of days from first capsule-opening up to days to 90% maturity, while the evaluated genotypes showed non-significant difference (P>0.05) for rate of shattering and other shattering-related traits which indicated low scope of improvement for shattering resistance through the evaluation and selection of landraces. Furthermore, low estimates of heritability and genetic advance as percentage of the mean for shattering and its related traits indicated that an environment had a significant influence on these traits, which suggests breeders to evaluate sesame genotypes for shattering resistance based on molecular data rather than phenotypic data for reliable results and valid recommendations.
Abstract: Shattering has a substantial yield reduction in sesame. Sixty-four sesame genotypes were evaluated using 8 x 8 lattice design with two replications at the main research station of Pawe Agricultural Research Center to assess the genetic variability among sesame genotypes for shattering and shattering-related traits. Data were collected on days to fi...
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Research Article
Evaluation of Food Barley (Hordeum vulgare L.) Varieties at Highlands of Southwestern Part of Ethiopia Using AMMI and GGE Biplot Stability Models
Issue:
Volume 11, Issue 4, December 2023
Pages:
126-132
Received:
13 November 2023
Accepted:
30 November 2023
Published:
8 December 2023
Abstract: A multi location trial was conducted across the highlands of Southwestern (SW) Ethiopia from 2020 to 2022 during main cropping seasons to evaluate grain yield and yield related traits of food barley varieties across the different locations to identify and recommend high yielding and stable food barley varieties to farmers for large scale planting using AMMI and GGE biplot models. A total of eight food barley varieties were obtained from the Sinana Agricultural Research Center (SARC) for use in this study. Varieties were evaluated in three environments, over three growing seasons. The experiments were conducted at Dedo, Yem and Gechi districts of SW part of Ethiopia during the main cropping seasons. The experiment was laid out in RCBD with three replications. The experimental plot for each variety consisted of six rows of 2.5m length and rows were spaced 20cm apart. Spacing between rows, plots and replications 25cm, 30cm and 1m respectively. Data for all relevant agronomic traits were collected, but only plot yield data converted to t/ha was subjected to statistical analysis. The combined ANOVA showed highly significant differences (P<0.001) among E, G and GEI for grain yield. The environmental variance was more accountable (68.2%) to the total variance as compared to the genetic variance (3.16%) and the interaction variance (19.13%) for grain yield. Dedo 2022 was the highest yielding (4.1 t/ha) while Gechi 2022 was the lowest yielding (1.5 t/ha) environment. The mean grain yield of the varieties across eight environments was 3 t/ha. The GGE biplot identified two barley growing mega-environments. The first mega environment consisted of environments E5, E8, E1 with a vertex genotype T4. E6, E4, E3, E2 and E7 were found in the second mega environment with the winning genotype of T8. It was also noted that no mega-environments fell into sectors where genotype T2 and T7 were the vertex genotypes, did not fit in any of the mega-environments. According to both AMMI and GGE biplot analysis, food barley varieties T3, T7 and T5 were found to be benchmarks/ideal genotypes and could be used as checks to evaluate the performance of other genotypes and also can be recommended for wider cultivation in the highland environments of Southwestern Ethiopia.
Abstract: A multi location trial was conducted across the highlands of Southwestern (SW) Ethiopia from 2020 to 2022 during main cropping seasons to evaluate grain yield and yield related traits of food barley varieties across the different locations to identify and recommend high yielding and stable food barley varieties to farmers for large scale planting u...
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Research Article
Construction of a Cuproptosis-Related Gene Clinical Prediction Model for Juvenile Idiopathic Arthritis Using Machine Learning
Yiwei Hong,
Xu Cai,
Xinpeng Chen,
Xinmin Huang,
Zhengbo Yan,
Peihu Li,
Jianwei Xiao*
Issue:
Volume 11, Issue 4, December 2023
Pages:
133-138
Received:
23 November 2023
Accepted:
7 December 2023
Published:
22 December 2023
Abstract: Objective: Juvenile Idiopathic Arthritis (JIA) is a chronic inflammatory joint disease affecting children and adolescents, where early diagnosis and treatment are crucial for improving prognosis. This study aimed to identify cuproptosis-related genes in JIA and develop a clinical predictive model. Methods: The GSE13849 dataset was retrieved from the GEO database to extract cuproptosis-related genes. Key JIA genes were selected using the Boruta and SVM-REF algorithms, followed by the construction of a clinical prediction model. The model's predictive capacity was validated using the concordance index (C-index), Receiver Operating Characteristic (ROC) curves, and calibration curves. Patient net benefit was evaluated through clinical decision curves, with internal validation conducted via Bootstrap. Results: The Boruta and SVM-REF algorithms identified four and five core cuproptosis-related genes, respectively, intersecting to yield three core genes (PDHA1, LIAS, DLAT). A clinical prediction model was established using multivariate logistic regression, exhibiting a C-index of 0.75 and an area under the ROC curve of 0.749. Clinical decision curve analysis demonstrated the highest net clinical benefit at a threshold probability range of 0.15 to 0.9, ensuring no harm to other patients. Internal validation reported a C-index of 0.755 and an area under the ROC curve of 0.736. Conclusion: The JIA clinical prediction model, based on three cuproptosis-related genes, demonstrates substantial predictive diagnostic capability, contributing to the early diagnosis of JIA patients.
Abstract: Objective: Juvenile Idiopathic Arthritis (JIA) is a chronic inflammatory joint disease affecting children and adolescents, where early diagnosis and treatment are crucial for improving prognosis. This study aimed to identify cuproptosis-related genes in JIA and develop a clinical predictive model. Methods: The GSE13849 dataset was retrieved from th...
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