Prabuddha Manjula U.D

Dr. Prabuddha Manjula U.D

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Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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31 July 2021 in Journal of Animal Science and Technology
Verified
Journal Article
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ECEunjin Cho
Eunjin Cho
MKMinjun Kim
Minjun Kim
PUPrabuddha Manjula U.D
Prabuddha Manjula U.D
SCSunghyun Cho
Sunghyun Cho
DSDongwon Seo
Dongwon Seo
Jun–Heon LeeJun–Heon Lee
Jun–Heon Lee
Journal of Animal Science and Technology (JAST) is a peer-reviewed, open access journal publishing original research, review articles and notes in all fields of animal science. Topics covered by the journal include: genetics and breeding, physiology, nutrition of monogastric animals, nutrition of ruminants, animal products (milk, meat, eggs and their by-products) and their processing, grasslands and roughages, livestock environment, animal biotechnology, animal behavior and welfare.

1 November 2020 in Asian-Australasian Journal of Animal Sciences
Verified
Journal Article
Open access
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MRMuhammad Abdur Rashid
Muhammad Abdur Rashid
PUPrabuddha Manjula U.D
Prabuddha Manjula U.D
SFShakila Faruque
Shakila Faruque
ABA. K. Fazlul Haque Bhuiyan
A. K. Fazlul Haque Bhuiyan
DSDongwon Seo
Dongwon Seo
MBMohammad Bhuiyan
Mohammad Bhuiyan
Objective: The objectives of this study were to investigate the genetic diversity, population structure and relatedness among the five chicken populations of Bangladesh using microsatellite markers.Methods: A total of 161 individuals representing 5 chicken populations (non-descript Deshi [ND], naked neck [NN], hilly [HI], Aseel [AS], and red jungle fowl [JF]) were included in this study to investigate genetic diversity measures, population structure, genetic distance and phylogenetic relationships. Genotyping was performed using 16 selected polymorphic microsatellite markers distributed across 10 chromosomes.Results: The average observed and expected heterozygosity, mean number of alleles and polymorphic information content were found to be 0.67±0.01, 0.70±0.01, 10.7 and 0.748, respectively in the studied populations. The estimated overall fixation index across the loci (F), heterozygote deficiency within (FIS) and among (FIT) chicken populations were 0.04±0.02, 0.05 and 0.16, respectively. Analysis of molecular variance analysis revealed 88.07% of the total genetic diversity was accounted for within population variation and the rest 11.93% was incurred with population differentiation (FST). The highest pairwise genetic distance (0.154) was found between ND and AS while the lowest distance was between JF and AS (0.084). Structure analysis depicted that the studied samples can be categorized into four distinct types or varieties (ΔK = 3.74) such as ND, NN, and HI where AS and JF clustered together as an admixed population. The Neighbor-Joining phylogenetic tree and discriminant analysis of principal component also showed close relatedness among three chicken varieties namely AS, HI, and JF.Conclusion: The results reflected that indigenous chicken of Bangladesh still possess rich genetic diversity but weak differentiation among the studied populations. This finding provides some important insight on genetic diversity measures that could support the designing and implementing of future breeding plans for indigenous chickens of Bangladesh.

1 June 2020 in Asian-Australasian Journal of Animal Sciences
Verified
Journal Article
Open access
OGOnolragchaa Ganbold
Onolragchaa Ganbold
SLSeung-Hwan Lee
Seung-Hwan Lee
WPWoon Kee Paek
Woon Kee Paek
MMMunkhbaatar Munkhbayar
Munkhbaatar Munkhbayar
DSDongwon Seo
Dongwon Seo
Jun–Heon LeeJun–Heon Lee
Jun–Heon Lee
Objective: Mongolia is one of a few countries that supports over 25 million goats, but genetic diversity, demographic history, and the origin of goat populations in Mongolia have not been well studied. This study was conducted to assess the genetic diversity, phylogenetic status and population structure of Mongolian native goats, as well as to discuss their origin together with other foreign breeds from different countries using hypervariable region 1 (HV1) in mtDNA.Methods: In this study, we examined the genetic diversity and phylogenetic status of Mongolian native goat populations using a 452 base-pair long fragment of HVI of mitochondrial DNA from 174 individuals representing 12 populations. In addition, 329 previously published reference sequences from different regions were included in our phylogenetic analyses.Results: Investigated native Mongolian goats displayed relatively high genetic diversities. After sequencing, we found a total of 109 polymorphic sites that defined 137 haplotypes among investigated populations. Of these, haplotype and nucleotide diversities of Mongolian goats were calculated as 0.997±0.001 and 0.0283±0.002, respectively. These haplotypes clearly clustered into four haplogroups (A, B, C, and D), with the predominance of haplogroup A (90.8%). Estimates of pairwise differences (Fst) and the analysis of molecular variance values among goat populations in Mongolia showed low genetic differentiation and weak geographical structure. In addition, Kazakh, Chinese (from Huanghuai and Leizhou), and Arabian (Turkish and Baladi breeds) goats had smaller genetic differentiation compared to Mongolian goats.Conclusion: In summary, we report novel information regarding genetic diversity, population structure, and origin of Mongolian goats. The findings obtained from this study reveal that abundant haplogroups (A to D) occur in goat populations in Mongolia, with high levels of haplotype and nucleotide diversity.


1 May 2018 in Asian-Australasian Journal of Animal Sciences
Verified
Journal Article
Open access
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PUPrabuddha Manjula U.D
Prabuddha Manjula U.D
NCNuri Choi
Nuri Choi
DSDongwon Seo
Dongwon Seo
Jun–Heon LeeJun–Heon Lee
Jun–Heon Lee
POU class 1 homeobox 1 (POU1F1) mediates growth hormone expression and activity by altering transcription, eventually resulting in growth rate variations. Therefore, we aimed to identify chicken POU1F1 polymorphisms and evaluate the association between single nucleotide polymorphisms (SNPs) and growth-related traits, and logistic growth curve parameter traits (α, β, and γ). Three SNPs (M_1 to M_3) were used to genotype 585 F1 and 88 F0 birds from five Korean native chicken lines using a polymerase chain reaction-restriction fragment length polymorphism method. Single marker analyses and traits association analyses showed that M_2 was significantly associated with body weight at two weeks, weight gain from hatch to 2 weeks, and weight gain from 16 to 18 weeks (p<0.05). M_3 was significantly associated with weight gain from 14 to 16 weeks and from 16 to 18 weeks, and asymptotic body weight (α) (p<0.05). No traits were associated with M_1. The POU1F1 haplogroups were significantly associated with weight gain from 14 to 16 weeks (p = 0.020). Linkage disequilibrium test and Haploview analysis shown one main haploblock between M_2 and M_3 SNP. Thus, POU1F1 significantly affects the growth of Korean native chickens and their growth curve traits.

1 August 2018 in Asian-Australasian Journal of Animal Sciences
Verified
Journal Article
Open access
PDF file
JSJin Shil
Jin Shil
HPHee-Bok Park
Hee-Bok Park
DSDongwon Seo
Dongwon Seo
NCNu Ri Choi
Nu Ri Choi
PUPrabuddha Manjula U.D
Prabuddha Manjula U.D
Jun–Heon LeeJun–Heon Lee
Jun–Heon Lee
Objective: Fatty acid composition is one of the most important meat quality traits because it can contribute to functional, sensorial, and nutritional factors. In this study, quantitative trait locus (QTL) analyses for fatty acid composition traits were investigated in thigh and breast meat of Korean native chicken (KNC). Methods: In total, 18 fatty acid composition traits were investigated from each meat sample using 83 parents, and 595 F-1 chicks of 20 week old. Genotype assessment was performed using 171 informative DNA markers on 26 autosomes. The KNC linkage map was constructed by CRI-MAP software, which calculated genetic distances, with map orders between markers. The half-sib and full-sib QTL analyses were performed using GridQTL and SOLAR programs, respectively. Results: In total, 30 QTLs (12 in the thigh and 18 in the breast meat) were detected by the half-sib analysis and 7 QTLs (3 in the thigh and 4 in the breast meat) were identified by the full-sib analysis. Conclusion: With further verification of the QTL regions using additional markers and positional candidate gene studies, these results can provide valuable information for determining causative mutations affecting the fatty acid composition of KNC meat. Moreover, these findings may aid in the selection of birds with favorable fatty acid composition traits.