RESUMEN

The BG line, originated by crossing 2 Chinese indigenous breeds, Dongxiang blue eggshell and Jiangshan black-bone, has been bred for black carcass and blue-greenish eggs. Aiming to study the genetic parameters and selection aspects of these eggshell colors, the 4 colorimeter parameters (L*, a*, b*, SCI = L*-a*-b*) were measured on ∼5 eggs/hen/age (200 d and 300 d) from each hen in 3 generations (G4 = 452, G5 = 508, G6 = 498). Visual eggshell color was classified as either "Light," "Blue," "Green," or "Olive," and data from G4 and G5 indicated that visual eggshell color was more accurately determined by combining the classifications of single representative egg/hen by 4 independent observers. Based on the apparent gradual variation in visual color, the 4 colors were expressed numerically (Light = 1, Blue = 2, Green = 3, Olive = 4) and the averages of the 4 observers (AveObs) were used as quantitative expression of the visual color of each egg. This expression, in the range from Blue to Olive, was highly significantly correlated with L*, b* and SCI. The a* values were also associated with AveObs, but not linearly; AveObs between 2 (Blue) and 3 (Green) had lowest a*, and it increased as AveObs was more Light (<2) or more Olive (>3). The heritability estimates of the colorimeter parameters were mostly very high; those of b* and SCI ranged between 0.7 and 0.8, and those of L* and a* between 0.6 and 0.7, indicating that they can serve as criterions to select for blue and/or green eggshells. The phenotypic and genetic correlations between the colorimeter parameters were highly significant and favorable. It is suggested that effective breeding for blue eggs can be done by selecting hens laying eggs with highest SCI/L* or lowest b* (against green and olive shades), followed by selection for low a* (against light shades). Breeding for green eggs can be done by selecting hens laying eggs with SCI ≈ 75 and/or L* ≈ 80 and/or b* ≈ 12. Breeding for hens that lay either blue or green eggs can be done by selection for low a* values.

RESUMEN

The BG line was originated from the cross between 2 Chinese indigenous breeds, Dongxiang blue eggshell, and Jiangshan black-bone, and has been bred to combine dark heavy black-bone body and high production of blue-shell eggs, into single dual-purpose line. Full-pedigree hens from 2 generations, G4 (n = 441) and G5 (n = 464), were reared in the same single-cage laying facility in 2019-2020 and 2020-2021, respectively. Starting from the first egg of each hen, its daily egg production was recorded until 300 days-of-age. Up to 7 "no-egg" days were considered normal laying breaks between clutches, whereas laying cessation of 8 or more days was considered Pause, and the laying pattern of each hen was assigned either with Pause or No-Pause. The other traits included PsDays: number of Pause days; AFE: age at first egg; EN300: eggs laid until 300 d; %L300: total laying rate (EN300/[300-AFE]); %Lnet: net laying rate (EN300/[300-AFE-PsDays]); ClLng: average clutch length; EW200 and EW300: average egg weight around 200 d and 300 d. Estimates of heritability (h2) of each trait, and phenotypic and genetic correlation between traits, were calculated in each generation using the animal model. Heritability estimates were calculated also by regressing the means of full-sib G5 hens on their G4 parents' means. Mean overall laying rate of all G4 hens was low (%L300 = 57%) because 53% of them had Pause in their laying pattern. In G5, incidence of Pause was higher (75%) due to a 3-wk cold stress, with mean %L300 = 54%. However, significant estimates of heritability and genetic correlations suggest that selection for low PsDays will reduce the incidence of Pause in BG hens and elevate the line's mean laying rate towards %L300 = 70%, as the No-Pause hens in G5. PsDays-free laying rate (%Lnet) was found to be highly correlated with the significantly heritable (h2≈0.4) clutch length (ClLng). Selection index combining the genetically independent low PsDays and high ClLng is expected to maximize egg production improvement in the BG line, and in similar populations derived from indigenous breeds.

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RESUMEN

An experimental population of chickens was developed from the cross between 2 indigenous Chinese breeds, Dongxiang blue eggshell and Jiangshan black-bone. This breeding was aimed at eventually combining dark heavy black-bone body and blue eggshell, into a single dual-purpose breed. BW was recorded and skin L∗, a∗, and b∗ color parameters were measured by a Chroma Meter at several ages (56, 105, 150, 200, 250, and 300 d). At 250 d, 3 independent observers classified skin darkness using a 3-level visual scale (1 = light, 2 = intermediate, 3 = dark). The 7-level average visual skin darkness, calculated for each chicken, was highly correlated (-0.658 and -0.612 in females and males, respectively) with skin L∗ (lightness), indicating that the accurately measured L∗ is reliable and useful reverse expression of visual skin darkness of black-bone chickens. Mean BW and skin L∗ of both sexes increased with age, to 2,063 and 1,522 g in males and females, respectively, at 300 d, and to 63 and 55 L∗ units in males and females, respectively, at 250 d. The population's full-pedigree allowed estimating heritability and genetic correlations between traits. The heritability estimates of BW were similar in both sexes, increasing from around 0.25 at 56 d, to 0.53 to 0.60 at 150 d, and 0.57 to 0.62 at 300 d. Over the 5 ages, heritability estimates of skin L∗ were moderate to high, ranging from 0.45 to 0.58 in females, and from 0.31 to 0.65 in males, and the genetic correlations between BW and L∗ ranged mostly from 0.20 to 0.45. These low-to-moderate correlations between high BW and high L∗ (low darkness) are unfavorable; hence they were combined into an index, standardized BW minus standardized L∗, allowing future selection for high BW with low L∗. With high heritability of this index, 0.487 (females at 300 d) and 0.410 to 0.555 (males at 150 d or older), simultaneous improvements in BW and skin darkness appear to be feasible. The methodology used in this study can be useful in chicken populations experimentally bred for combination of high BW and other body characteristics.

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RESUMEN

Prediction of protein structural class plays an important role in protein structure and function analysis, drug design and many other biological applications. Prediction of protein structural class for low-similarity sequences is still a challenging task. Based on the theory of wavelet denoising, this paper presents a novel method of prediction of protein structural class for the first time. Firstly, the features of the protein sequence are extracted by using Chou's pseudo amino acid composition (PseAAC). Then the extracted feature information is denoised by two-dimensional (2D) wavelet. Finally, the optimal feature vectors are input to support vector machine (SVM) classifier to predict protein structural classes. We obtained significant predictive results using jackknife test on three low-similarity protein structural class datasets 25PDB, 1189 and 640, and compared our method with previous methods The results indicate that the method proposed in this paper can effectively improve the prediction accuracy of protein structural class, which will be a reliable tool for prediction of protein structural class, especially for low-similarity sequences.

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