Revisiting avian 'missing' genes from de novo assembled transcripts.

BACKGROUND: Argument remains as to whether birds have lost genes compared with mammals and non-avian vertebrates during speciation. High quality-reference gene sets are necessary for precisely evaluating gene gain and loss. It is essential to explore new reference transcripts from large-scale de novo assembled transcriptomes to recover the potential hidden genes in avian genomes. RESULTS: We explored 196 high quality transcriptomic datasets from five bird species to reconstruct transcripts for the purpose of discovering potential hidden genes in the avian genomes. We constructed a relatively complete and high-quality bird transcript database (1,623,045 transcripts after quality control in five birds) from a large amount of avian transcriptomic data, and found most of the presumed missing genes (83.2%) could be recovered in at least one bird species. Most of these genes have been identified for the first time in birds. Our results demonstrate that 67.94% genes have GC content over 50%, while 2.91% genes are AT-rich (AT% > 60%). In our results, 239 (53.59%) genes had a tissue-specific expression index of more than 0.9 in chicken. The missing genes also have lower Ka/Ks values than average (genome-wide: Ka/Ks = 0.99; missing gene: Ka/Ks = 0.90; t-test = 1.25E-14). Among all presumed missing genes, there were 135 for which we did not find any meaningful orthologues in any of the 5 species studied. CONCLUSION: Insufficient reference genome quality is the major reason for wrongly inferring missing genes in birds. Those presumably missing genes often have a very strong tissue-specific expression pattern. We show multi-tissue transcriptomic data from various species are necessary for inferring gene family evolution for species with only draft reference genomes.

In vivo prediction of the carcass fatness using live body measurements in Pekin ducks.

The purpose of this study was to evaluate the correlation between live body measurements and several fat traits in Pekin ducks, and ultimately to formulate multiple regression equations for the in vivo estimation of the carcass fatness of Pekin ducks. Several traits were measured in a total of 208 Pekin ducks aged 6 wk (107 males and 101 females). All ducks were weighed and measured for a set of body measurements including live body weight, body slope length, breast muscle thickness, skin fat thickness, chest width, keel length, and neck length. The breast muscle thickness and skin fat thickness was measured using B-scan sonography. Carcass information, including eviscerated weight, subcutaneous fat with skin weight, and abdominal fat weight, was collected after slaughter. Our results revealed that sex effects on most traits were significant (P < 0.05), and that the weight of subcutaneous fat with skin was significantly correlated with live body weight (r = 0.57 to 0.71, P < 0.01). Four additional traits of males were closely correlated with the weight of subcutaneous fat with skin, namely breast muscle thickness (r = 0.20, P < 0.01), skin fat thickness (r = 0.43, P < 0.01), chest width (r = 0.24, P < 0.01), and neck length (r = 0.20, P < 0.05). The abdominal fat weight, percentage of fat, and percentage of subcutaneous fat with skin of ducks were significantly correlated with live body weight (r = 0.38 to 0.43, P < 0.01), and skin fat thickness (r = 0.38 to 0.49, P < 0.01). These traits provided the basis for constructing regression equations to predict weight (or percentage) of subcutaneous fat and abdominal fat with high values of coefficients of multiple correlation (R) between the dependent variable and the independent variables. Two equations were verified to be applicable in other duck groups, with high accuracy, as more than 80% of estimated values were within the margin of error (<10%), compared with the actual values.