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Broken and cracked eggshells are major causes of significant economic losses to the egg production industry. The quantitative trait loci (QTL) on chromosome 9 influencing the quality of eggshells were identified by analysing an intercross between two parent lines developed from the same founder population by a two-way selection for eggshell strength with non-destructive deformation conducted over 14 generations. Chromosome-wide highly significant (P < 0.01) QTL associated with egg weight (EW), short length of egg (SLE), long length of egg (LLE) and eggshell weight were mapped to the distal region of chromosome 9. Among the QTL affecting EW, SLE and LLE, ovocalyxin-32 was identified as a potential candidate gene influencing eggshell traits. Marker-assisted selection based on these QTL could be used to develop strategies for reducing the breakage and cracking of eggs in commercial layer houses.

We constructed a chicken F(2) resource population to facilitate the genetic improvement of economically important traits, particularly growth and carcass traits. An F(2) population comprising 240 chickens obtained by crossing a Shamo (lean, lightweight Japanese native breed) male and White Plymouth Rock breed (fat, heavyweight broiler) females was measured for BW, carcass weight (CW), abdominal fat weight (AFW), breast muscle weight (BMW), and thigh muscle weight (TMW) and was used for genome-wide linkage and QTL analysis, using a total of 240 microsatellite markers. A total of 14 QTL were detected at a 5% chromosome-wide level, and 7 QTL were significant at a 5% experiment-wide level for the traits evaluated in the F(2) population. For growth traits, significant and suggestive QTL affecting BW (measured at 6 and 9 wk) and average daily gain were identified on similar regions of chromosomes 1 and 3. For carcass traits, the QTL effects on CW were detected on chromosomes 1 and 3, with the greatest F-ratio of 15.0 being obtained for CW on chromosome 3. Quantitative trait loci positions affecting BMW and TMW were not detected at the same loci as those detected for BMW percentage of CW and TMW percentage of CW. For AFW, QTL positions were detected at the same loci as those detected for AFW percentage of CW. The present study identified significant QTL affecting BW, CW, and AFW.

A genome-wide scan for QTL affecting economically important traits in beef production was performed using an F(2) resource family from a Japanese Black x Limousin cross, where 186 F(2) animals were measured for growth, carcass, and meat-quality traits. All family members were genotyped for 313 informative microsatellite markers that spanned 2,382 cM of bovine autosomes. The centromeric region of BTA2 contained significant QTL (i.e., exceeding the genome-wide 5% threshold) for 5 carcass grading traits [LM area, beef marbling standards (BMS) number, luster, quality grade, and firmness), 8 computer image analysis (CIA) traits [LM lean area, ratio of fat area (RFA) to LM area, LM area, RFA to musculus (M.) trapezius area, M. trapezius lean area, M. semispinalis lean area, RFA to M. semispinalis area, and RFA to M. semispinalis capitis area], and 5 meat quality traits (contents of CP, crude fat, moisture, C16:1, and C18:2 of LM). A significant QTL for withers height was detected at 80.3 cM on BTA5. We detected significant QTL for the C14:0 content in backfat and C14:0 and C14:1 content in intermuscular fat around the 62.3 to 71.0 cM region on BTA19 and for C14:0, C14:1, C18:1, and C16:0 content and ratio of total unsaturated fatty acid content to total SFA content in intramuscular fat at 2 different regions on BTA19 (41.1 cM for C14:1 and 62.3 cM for the other 4 traits). Overall, we identified 9 significant QTL regions controlling 27 traits with genome-wide significance of 5%; of these, 22 traits exceeded the 1% genome-wide threshold. Some of the QTL affecting meat quality traits detected in this study might be the same QTL as previously reported. The QTL we identified need to be validated in commercial Japanese Black cattle populations.

Understanding of the genetic control of female reproductive performance in pigs would offer the opportunity to utilize natural variation and improve selective breeding programs through marker-assisted selection. The Chinese Meishan is one of the most prolific pig breeds known, farrowing 3 to 5 more viable piglets per litter than Western breeds. This difference in prolificacy is attributed to the Meishan's superior prenatal survival. Our study utilized a 3-generation resource population, in which the founder grandparental animals were purebred Meishan and Duroc pigs, in a genome scan for QTL. Grandparent, F1, and F2 animals were genotyped for 180 microsatellite markers. Reproductive traits, including number of corpora lutea (number of animals = 234), number of fetuses per animal (n = 226), number of teats (n = 801), and total number born (n = 288), were recorded for F2 females. Genome-wide significance level thresholds of 1, 5, and 10% were calculated using a permutation approach. We identified 9 QTL for 3 traits at a 10% genome-wise significance level. Parametric interval mapping analysis indicated evidence of a 1% genome-wise significant QTL for corpora lutea on SSC 3. Nonparametric interval mapping for number of teats found 4 significant QTL on chromosomes SSC3 (P < 0.01), SSC7 (P < 0.01), SSC8 (P < 0.01), and SSC12 (P < 0.05). Partial imprinting of a QTL affecting teat number (P < 0.10) was detected on SSC8. Using the likelihood-ratio test for a categorical trait, 2 QTL for pin nipples were detected on SSC2 and SSC16 (P < 0.01). Fine mapping of the QTL regions will be required for their application to introgression programs and gene cloning.

Phenotypic measurements of chicken egg character and production traits are restricted to mature females only. Marker assisted selection of immature chickens using quantitative trait loci (QTL) has the potential to accelerate the genetic improvement of these traits in the chicken population. The QTL for 12 traits (i.e. body weight (BW), six for egg character, three for egg shell colour and two for egg production) of chickens were identified. An F2 population comprising 265 female chickens obtained by crossing White Leghorn and Rhode Island Red breeds and genotyped for 123 microsatellite markers was used for detecting QTL. Ninety-six markers were mapped on 25 autosomal linkage groups, and 13 markers were mapped on one Z chromosomal linkage group. Eight previous unmapped markers were assigned to their respective chromosomes in this study. Significant QTL were detected for BW on chromosomes 4 and 27, egg weight on chromosome 4, the short length of egg on chromosome 4, and redness of egg shell colour (using the L*a*b* colour system) on chromosome 11. A significant QTL on the Z chromosome was linked with age at first egg. Significant QTL could account for 6-19% of the phenotypic variance in the F2 population.

We constructed a pig F2 resource population by crossing a Meishan sow and a Duroc boar to locate economically important trait loci. The F2 generation was composed of 865 animals (450 males and 415 females) from four F1 males and 24 F1 females and was genotyped for 180 informative microsatellite markers spanning 2,263.6 cM of the whole pig genome. Results of the genome scan showed evidence for significant quantitative trait loci (<1% genomewise error rate) affecting weight at 30 d and average daily gain on Sus scrofa chromosome (SSC) 6, carcass yield on SSC 7, backfat thickness on SSC 7 and SSC X, vertebra number on SSC 1 and SSC 7, loin muscle area on SSC 1 and SSC 7, moisture on SSC 13, intramuscular fat content on SSC 7, and testicular weight on SSC 3 and SSC X. Moreover, 5% genomewise significant QTL were found for birth weight on SSC 7, average daily gain on SSC 4, carcass length on SSC 6, SSC 7, and SSC X and lightness (L value) on SSC 3. We identified 38 QTL for 28 traits at the 5% genomewise level. Of the 38 QTL, 24 QTL for 17 traits were significant at the 1% genomewise level. Analysis of marker genotypes supported the breed of origin results and provided further evidence that a suggestive QTL for circumference of cannon bone also was segregating within the Meishan parent. We identified genomic regions related with growth and meat quality traits. Fine mapping will be required for their application in introgression programs and gene cloning.

Broken and cracked eggshells are major causes of significant economic losses to the egg production industry. The quantitative trait loci (QTL) on chromosome 9 influencing the quality of eggshells were identified by analysing an intercross between two parent lines developed from the same founder population by a two-way selection for eggshell strength with non-destructive deformation conducted over 14 generations. Chromosome-wide highly significant ( P < 0.01) QTL associated with egg weight (EW), short length of egg (SLE), long length of egg (LLE) and eggshell weight were mapped to the distal region of chromosome 9. Among the QTL affecting EW, SLE and LLE, ovocalyxin-32 was identified as a potential candidate gene influencing eggshell traits. Marker-assisted selection based on these QTL could be used to develop strategies for reducing the breakage and cracking of eggs in commercial layer houses. [ABSTRACT FROM AUTHOR]

A genome-wide scan for QTL affecting economically important traits in beef production was performed using an F2 resource family from a Japanese Black × Limousin cross, where 186 F2 animals were measured for growth, carcass, and meat-quality traits. All family members were genotyped for 313 informative microsatellite markers that spanned 2,382 cM of bovine autosomes. The centromeric region of BTA2 contained significant QTL (i.e., exceeding the genomewide 5% threshold) for 5 carcass grading traits [LM area, beef marbling standards (BMS) number, luster, quality grade, and firmness), 8 computer image analysis (CIA) traits [LM lean area, ratio of fat area (RFA) to LM area, LM area, RFA to musculus (M.) trapezius area, M. trapezius lean area, M. semispinalis lean area, RFA to M. semispinalis area, and RFA to M. semispinalis capitis area], and 5 meat quality traits (contents of CP, crude fat, moisture, C16:1, and C18:2 of LM). A significant QTL for withers height was detected at 80.3 cM on BTA5. We detected significant QTL for the C 14:0 content in backfat and C14:0 and C 14:1 content in intermuscular fat around the 62.3 to 71.0 cM region on BTA19 and for C14:0, C14:1, C18:1, and C16:0 content and ratio of total unsaturated fatty acid content to total SFA content in intramuscular fat at 2 different regions on BTA19 (41.1 cM for C14:1 and 62.3 cM for the other 4 traits). Overall, we identified 9 significant QTL regions controlling 27 traits with genomewide significance of 5%; of these, 22 traits exceeded the 1% genome-wide threshold. Some of the QTL affecting meat quality traits detected in this study might be the same QTL as previously reported. The QTL we identified need to be validated in commercial Japanese Black cattle populations. [ABSTRACT FROM AUTHOR]

Understanding of the genetic control of female reproductive performance in pigs would offer the opportunity to utilize natural variation and improve selective breeding programs through marker-assisted selection. The Chinese Meishan is one of the most prolific pig breeds known, farrowing 3 to 5 more viable piglets per litter than Western breeds. This difference in prolificacy is attributed to the Meishan's superior prenatal survival. Our study utilized a 3-generation resource population, in which the founder grandparental animals were purebred Meishan and Duroc pigs, in a genome scan for QTL. Grandparent, F1, and F2 animals were genotyped for 180 microsatellite markers. Reproductive traits, including number of corpora lutea (number of animals = 234), number of fetuses per animal (n = 226), number of teats (n = 801), and total number born (n = 288), were recorded for F2 females. Genome- wide significance level thresholds of 1, 5, and 10% were calculated using a permutation approach. We identified 9 QTL for 3 traits at a 10% genome-wise significance level. Parametric interval mapping analysis indicated evidence of a 1% genome-wise significant QTL for corpora lutea on SSC 3. Nonparametric interval mapping for number of teats found 4 significant QTL on chromosomes SSC3 (P < 0.01), SSC7 (P < 0.01), SSC8 (P < 0.01), and SSC12 (P < 0.05). Partial imprinting of a QTL affecting teat number (P < 0.10) was detected on SSC8. Using the likelihood-ratio test for a categorical trait, 2 QTL for pin nipples were detected on SSC2 and SSC16 (P < 0.01). Fine mapping of the QTL regions will be required for their application to introgression programs and gene cloning. [ABSTRACT FROM AUTHOR]