Scholarly Works, Fralin Life Sciences Institute
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Browsing Scholarly Works, Fralin Life Sciences Institute by Department "Animal and Poultry Sciences"
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- Advancing livestock genomics education and research in developing countries using strategies from the Virginia Tech PREP and IMSD training programsSmith, Edward J. (2019-07-11)Our unique and impactful research and education program plan includes distinct activities that target three overlapping phases of each trainee’s tenure, which we define as the “moving in,” “moving through,” and “moving out” phases. During the “moving in” phase, 8 trainees “who need a PREP” will be recruited and assigned to mentors using our proven strategy that is “scholar-driven” and combines mentor qualities such as prior experience, which has resulted in a 98% retention for each of our 3 funding cycles. $409,537 annually or ~2.1 Million for five years. our successful interdisciplinary Initiative for Maximizing Student Development (IMSD) program for pre-doctoral (graduate) and pre-baccalaureate (undergraduate) students from groups underrepresented in careers in the biomedical and behavioral sciences. Our training program is a partnership with departments and interdisciplinary graduate programs which takes advantage of Virginia Tech’s (VT) history of excellence in Engineering and the Behavioral and Life Sciences. With lessons learned in the last eight years, we will continue to recruit across disciplines and from diverse geographic areas and institutions. From the first cycle, 2007-12, a total of 23 pre-doctoral students participated in the VT IMSD program. A total of 16 (or 69.5%) have completed and received the PhD degree; Total Year 1: $467,489.
- Association of Polymorphisms in the Period3 (turPer3) Gene with Growth and Reproductive Traits in Turkeys (Meleagris gallopavo)Smith, E.; Adikari, A. M.; Xu, J. (2018)Background and objective: Biological clock controls behavioral, physiological and biochemical circadian rhythms of animals. Circadian clock genes including period3 are involved in the circadian clock mechanism. The present study was conducted to test the hypothesis that differences in DNA sequence variations of the turkey period3 (turPer3) gene may be associated with performance traits including growth and reproduction. Methodology: The turPer3 gene was screened for DNA sequence variations and evaluated the relationships among haplogroups with performance traits. The DNA sequences of turPer3 (16.6 kb) gene were screened using 290 turkey birds by re-sequencing the individual amplicons. Results: Seven SNPs, including one each in exon 18 and intron 5, two SNPs in exon 19 and three SNPs in intron 6, were detected. The SNPs detected in the exon 19 were non-synonymous, which changed the amino acids from methionine to threonine and serine to phenylalanine at 953rd and 955th positions, respectively. Linkage disequilibrium (Dʼ) among SNPs ranged from 0.03-1.00. Pairwise FST ranged from 0.01-0.43. Haplogroup frequencies of the turPer3 ranged from 0.02-1.00, were significantly associated with body weight (BW) at 231 days of age, average daily gain (ADG) for the period of 160-231 d of age, FCR for the periods of 69-159 d and 160-231 d, egg production and semen quality traits (p#0.05). Conclusion: The DNA sequence variations of turPer3 gene are significantly associated with BW, ADG, FCR, egg production, egg weight and semen quality traits. turPer3 gene may seem to have some regulatory role in the molecular mechanism of the circadian clock. Genomic reagents reported in the present study would be valuable for future genotype: phenotype evaluation studies in the turkey using a candidate gene approach.
- Body Weight Selection Affects Quantitative Genetic Correlated Responses in Gut MicrobiotaMeng, He; Zhang, Yan; Zhao, Lele; Zhao, Wenjing; He, Chuan; Honaker, Christa F.; Zhai, Zhengxiao; Sun, Zikui; Siegel, Paul B. (PLOS, 2014-03-07)The abundance of gut microbiota can be viewed as a quantitative trait, which is affected by the genetics and environment of the host. To quantify the effects of host genetics, we calculated the heritability of abundance of specific microorganisms and genetic correlations among them in the gut microbiota of two lines of chickens maintained under the same husbandry and dietary regimes. The lines, which originated from a common founder population, had undergone >50 generations of selection for high (HW) or low (LW) 56-day body weight and now differ by more than 10-fold in body weight at selection age. We identified families of Paenibacillaceae, Streptococcaceae, Helicobacteraceae, and Burkholderiaceae that had moderate heritabilities. Although there were no obvious phenotypic correlations among gut microbiota, significant genetic correlations were observed. Moreover, the effects were modified by genetic selection for body weight, which altered the quantitative genetic background of the host. Heritabilities for Bacillaceae, Flavobacteriaceae, Helicobacteraceae, Comamonadaceae, Enterococcaceae, and Streptococcaceae were moderate in LW line and little to zero in the HW line. These results suggest that loci associated with these microbiota families, while exhibiting genetic variation in LW, have been fixed in HW line. Also, long term selection for body weight has altered the genetic correlations among gut microbiota. No microbiota families had significant heritabilities in both the LW and HW lines suggesting that the presence and/or absence of a particular microbiota family either has a strong growth promoting or inhibiting effect, but not both. These results demonstrate that the quantitative genetics of the host have considerable influence on the gut microbiota.
- Multi-Platform Next-Generation Sequencing of the Domestic Turkey (Meleagris gallopavo): Genome Assembly and AnalysisDalloul, Rami A.; Long, Julie A.; Zimin, Aleksey V.; Aslam, Luqman; Beal, Kathryn; Blomberg, Le Ann; Bouffard, Pascal; Burt, David W.; Crasta, Oswald; Crooijmans, Richard P. M. A.; Cooper, Kristal; Coulombe, Roger A.; De, Supriyo; Delany, Mary E.; Dodgson, Jerry B.; Dong, Jennifer J.; Evans, Clive; Frederickson, Karin M.; Flicek, Paul; Florea, Liliana; Folkerts, Otto; Groenen, Martien A. M.; Harkins, Tim T.; Herrero, Javier; Hoffmann, Steve; Megens, Hendrik-Jan; Jiang, Andrew; de Jong, Pieter; Kaiser, Pete; Kim, Heebal; Kim, Kyu-Won; Kim, Sungwon; Langenberger, David; Lee, Mi-Kyung; Lee, Taeheon; Mane, Shrinivasrao P.; Marcais, Guillaume; Marz, Manja; McElroy, Audrey P.; Modise, Thero; Nefedov, Mikhail; Notredame, Cédric; Paton, Ian R.; Payne, William S.; Pertea, Geo; Prickett, Dennis; Puiu, Daniela; Qioa, Dan; Raineri, Emanuele; Ruffier, Magali; Salzberg, Steven L.; Schatz, Michael C.; Scheuring, Chantel; Schmidt, Carl J.; Schroeder, Steven; Searle, Stephen M. J.; Smith, Edward J.; Smith, Jacqueline; Sonstegard, Tad S.; Stadler, Peter F.; Tafer, Hakim; Tu, Zhijian Jake; Van Tassell, Curtis P.; Vilella, Albert J.; Williams, Kelly P.; Yorke, James A.; Zhang, Liqing; Zhang, Hong-Bin; Zhang, Xiaojun; Zhang, Yang; Reed, Kent M. (PLOS, 2010-09-01)A synergistic combination of two next-generation sequencing platforms with a detailed comparative BAC physical contig map provided a cost-effective assembly of the genome sequence of the domestic turkey (Meleagris gallopavo). Heterozygosity of the sequenced source genome allowed discovery of more than 600,000 high quality single nucleotide variants. Despite this heterozygosity, the current genome assembly (,1.1 Gb) includes 917 Mb of sequence assigned to specific turkey chromosomes. Annotation identified nearly 16,000 genes, with 15,093 recognized as protein coding and 611 as non-coding RNA genes. Comparative analysis of the turkey, chicken, and zebra finch genomes, and comparing avian to mammalian species, supports the characteristic stability of avian genomes and identifies genes unique to the avian lineage. Clear differences are seen in number and variety of genes of the avian immune system where expansions and novel genes are less frequent than examples of gene loss. The turkey genome sequence provides resources to further understand the evolution of vertebrate genomes and genetic variation underlying economically important quantitative traits in poultry. This integrated approach may be a model for providing both gene and chromosome level assemblies of other species with agricultural, ecological, and evolutionary interest.
- Quantitative Genetic Background of the Host Influences Gut Microbiomes in ChickensZhao, Lele; Wang, Gang; Siegel, Paul B.; He, Chuan; Wang, Hezhong; Zhao, Wenjing; Zhai, Zhengxiao; Tian, Fengwei; Zhao, Jianxin; Zhang, Hao; Sun, Zikui; Chen, Wei; Zhang, Yan; Meng, He (Nature Publishing Group, 2013-01)Host genotype and gender are among the factors that influence the composition of gut microbiota. We studied the population structure of gut microbiota in two lines of chickens maintained under the same husbandry and dietary regimes. The lines, which originated from a common founder population, had undergone 54 generations of selection for high (HW) or low (LW) 56-day body weight, and now differ by more than 10-fold in body weight at selection age. Of 190 microbiome species, 68 were affected by genotype (line), gender, and genotype by gender interactions. Fifteen of the 68 species belong to Lactobacillus. Species affected by genotype, gender, and the genotype by gender interaction, were 29, 48, and 12, respectively. Species affected by gender were 30 and 17 in the HW and LW lines, respectively. Thus, under a common diet and husbandry host quantitative genotype and gender influenced gut microbiota composite.