Hematological and Growth Performance Studies after Withania Somnifera Supplementation in Broilers

2016 ◽  
Vol 21 (1) ◽  
pp. 173-183
Author(s):  
Osama Abdallah ◽  
Omnia Killany ◽  
Heba El Gharib ◽  
Raghda Mohamed
Genes ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1203
Author(s):  
Sherif Melak ◽  
Qin Wang ◽  
Ye Tian ◽  
Wei Wei ◽  
Lifan Zhang ◽  
...  

Growth performance is a complex economic trait for avian production. The swan goose (Anser cygnoides) has never been exploited genetically like chickens or other waterfowl species such as ducks. Traditional phenotypic selection is still the main method for genetic improvement of geese body weight. In this study, specific locus amplified fragment sequencing (SLAF-seq) with bulked segregant analysis (BSA) was conducted for discovering and genotyping single nucleotide polymorphisms (SNPs) associated with marketing weight trait in male geese. A total of 149,045 SNPs were obtained from 427,093 SLAF tags with an average sequencing depth of 44.97-fold and a Q30 value of 93.26%. After SNPs’ filtering, a total of 12,917 SNPs were included in the study. The 31 highest significant SNPs—which had different allelic frequencies—were further validated by individual-based AS-PCR genotyping in two populations. The association between 10 novel SNPs and the marketing weight of male geese was confirmed. The 10 significant SNPs were involved in linear regression model analysis, which confirmed single-SNP associations and revealed three types of SNP networks for marketing weight. The 10 significant SNPs were located within or close to 10 novel genes, which were identified. The qPCR analysis showed significant difference between genotypes of each SNP in seven genes. Developed SLAF-seq and identified genes will enrich growth performance studies, promoting molecular breeding applications to boost the marketing weight of Chinese geese.


Aquaculture ◽  
1999 ◽  
Vol 173 (1-4) ◽  
pp. 285-296 ◽  
Author(s):  
Yaniv Hinits ◽  
Boaz Moav

2007 ◽  
Vol 6 (4) ◽  
pp. 248-250 ◽  
Author(s):  
S. Subapriya ◽  
S. Vairamuthu ◽  
B. Murali Man ◽  
C. Balachandr

Sign in / Sign up

Export Citation Format

Share Document