A predictive assessment of genetic correlations between traits in chickens using markers

International audienceAbstractBackgroundGenomic selection has been successfully implemented in plant and animal breeding programs to shorten generation intervals and accelerate genetic progress per unit of time. In practice, genomic selection can be used to improve several correlated traits simultaneously via multiple-trait prediction, which exploits correlations between traits. However, few studies have explored multiple-trait genomic selection. Our aim was to infer genetic correlations between three traits measured in broiler chickens by exploring kinship matrices based on a linear combination of measures of pedigree and marker-based relatedness. A predictive assessment was used to gauge genetic correlations.MethodsA multivariate genomic best linear unbiased prediction model was designed to combine information from pedigree and genome-wide markers in order to assess genetic correlations between three complex traits in chickens, i.e. body weight at 35 days of age (BW), ultrasound area of breast meat (BM) and hen-house egg production (HHP). A dataset with 1351 birds that were genotyped with the 600 K Affymetrix platform was used. A kinship kernel (K) was constructed as K = λG + (1 − λ)A, where A is the numerator relationship matrix, measuring pedigree-based relatedness, and G is a genomic relationship matrix. The weight (λ) assigned to each source of information varied over the grid λ = (0, 0.2, 0.4, 0.6, 0.8, 1). Maximum likelihood estimates of heritability and genetic correlations were obtained at each λ, and the “optimum” λ was determined using cross-validation.ResultsEstimates of genetic correlations were affected by the weight placed on the source of information used to build K. For example, the genetic correlation between BW–HHP and BM–HHP changed markedly when λ varied from 0 (only A used for measuring relatedness) to 1 (only genomic information used). As λ increased, predictive correlations (correlation between observed phenotypes and predicted breeding values) increased and mean-squared predictive error decreased. However, the improvement in predictive ability was not monotonic, with an optimum found at some 0 < λ < 1, i.e., when both sources of information were used together.ConclusionsOur findings indicate that multiple-trait prediction may benefit from combining pedigree and marker information. Also, it appeared that expected correlated responses to selection computed from standard theory may differ from realized responses. The predictive assessment provided a metric for performance evaluation as well as a means for expressing uncertainty of outcomes of multiple-trait selection

Importance of genotype by environment interaction on genetic analysis of milk yield in Iranian Holstein cows using a random regression model

Changes in the relative performance of genotypes (sires) across different environments, which are referred to as genotype–environment interactions, play an important role in dairy production systems, especially in countries that rely on imported genetic material. Importance of genotype by environment interaction on genetic analysis of milk yield was investigated in Holstein cows by using random regression model. In total, 68 945 milk test-day records of first, second and third lactations of 8515 animals that originated from 100 sires and 7743 dams in 34 herds, collected by the Iranian animal breeding centre during 2007–2009, were used. The different sires were considered as different genotypes, while factors such as herd size, herd milk average (HMA), herd protein average and herd fat average were used as criteria to define the different environments. The inclusion of the environmental descriptor improved not only the log-likelihood of the model, but also the Bayesian information criterion. The results showed that defining the environment on the basis of HMA affected genetic parameter estimations more than did the other environmental descriptors. The heritability of milk yield during lactating days reduced when sire · HMA was fitted to the model as an additional random effect, while the genetic and phenotypic correlations between lactating months increased. Therefore, ignoring this interaction term can lead to the biased genetic-parameter estimates, reduced selection accuracy and, thus, different ranking of the bulls in different environments

Inclusion of skin follicle traits in selection indices in breeding programs improves genetic gain in Australian fine-wool Merinos

Genetic parameters for skin follicle traits, wool traits, body weight, and number of lambs weaned per ewe joined were estimated for 5108 10-month-old Australian fine-wool Merinos born between 1990 and 1996. These animals were descended from 261 sires and 2508 dams. The skin follicle number index that is based on skin surface area, and primary, secondary, or total follicle density were introduced as possible early-age selection criteria estimated at 6 months of age. Heritability estimates for total, secondary, and primary follicle number index were 0.45±0.04, 0.46±0.04, and 0.38±0.04, respectively. The genetic correlations of total follicle number index with clean fleece weight, mean fibre diameter, staple strength, coefficient of variation of fibre diameter, body weight, and number of lambs weaned were 0.16, −0.67, 0.00, 0.03, 0.22, and 0.22, respectively. Responses to selection on indices including and excluding follicle traits were calculated based on the genetic parameters estimated, and with annual responses calculated using an optimised age structure. On average, 10% greater response was predicted when total follicle number index was used as an additional selection criterion in different micron premium scenarios. In comparison, skin follicle density had a smaller effect on genetic improvement. The extra response was ∼1%. Similar index responses were obtained when total follicle number index was used as a replacement selection criterion for clean fleece weight, mean fibre diameter, and coefficient of variation of fibre diameter for breeding objectives with low emphasis on fibre diameter. In objectives with high emphasis on fibre diameter, unfavourable correlated responses in staple strength and CV of fibre diameter limited the effectiveness of using total follicle number index as a selection criterion. Although the use of total follicle number index as an additional selection criterion can be favourable for some breeding objectives, measuring this trait is currently cost prohibitive to inclusion in Merino breeding programs

A genomic scan for detection of selection signatures using snp data in Australian merino sheep

Deciphering the genetic basis of phenotypic diversity is one of the main aims of biological research. Domestic animals are useful tool for making substantial progress towards this goal. Selection signatures are the regions of the genome that are functionally important and therefore have been under either natural or artificial selection. In this paper, a whole genome scan was performed using 3000 individuals, ~50000 SNP markers from nine populations of Australian Merino sheep, with the aim of identifying divergently selected regions of the genome. Five genomic regions on 4 chromosomes were identified as putatively harboring selective sweeps. These regions were located on chromosomes 6, 7, 11 (two areas) and 26. These selected genomic regions were surveyed to find encoding putative candidate genes and 9 genes were extracted from areas Ovine Genome v3.1 Assembly.Study of the reported QTL in these regions of the sheep genome showed that they overlapped with QTL of economically important traits such as carcass yield, growth and wool traits. Further investigation of these regions in validation studies will help to identify the candidate genes for economically important traits in sheep breeds

A genome-wide scan to detect signatures of recent selection in Australian Merino sheep

Domestication and selection are processes that conserve the pattern of genetic diversities between and within populations. Identification of genomic regions that are targets of selection for phenotypic traits is one of the main aims of research in animal genetics. An approach for identifying divergently selected regions of the genome is to compare FST values among loci to estimate the genetic variability between and within populations. In this study, a whole genome scan using the 50K Illumina Ovine SNP chip was performed in seventeen flocks of Australian Merino sheep (8 CRC flocks and 9 SG flocks). Population differentiation using FST in these flocks revealed seven genomic regions. These areas were located on chromosomes 2 (two region), 3, 6, 7, 16 and 26 (Wintheta&gt; 0.15). In this study, a number of candidate genes associated with reproductive and growth traits were identified. Study of the reported QTLs in these regions of the ovine and bovine genomes also showed that they associated with important traits such as reproduction, carcass yield, growth and wool traits. Further validation studies of these regions can be used to identify the candidate genes for economically important traits in sheep breeds. The results also provided intuitions for further understanding of the genetic diversities among the Merino flocks

Using PCR-SSCP technique to investigate polymorphism of leptin gene in Kermani sheep

شناسایی ژنهاي موثر بر تعادل انرژي، تولید شیر و مصرف خوراك از علاقهمنديهاي اخیر پژوهشگران اصلاح نژاداست. در ایران علی رغم وجود منابع غنی حیوانی، تلاشهاي اندکی براي شناسایی ژنهاي کنترل کنندهي صفات درآنها صورت گرفته است. بنابراین، شناسایی ژنهاي کاندیداي موثر بر صفات اقتصادي میتواند به اصلاح نژاد گوسفنددر کشور کمک شایانی نماید. در این تحقیق براي بررسی چند شکلی ژن لپتین از 120 رأس گوسفند نر و مادهي کرمانیایستگاه اصلاح نژاد شهر بابک خونگیري شد. پس از استخراج DNA با استفاده از کیت استخراج استاندارد، واکنشزنجیرهاي پلیمراز براي تکثیر قطعهي 275 جفت بازي از اگزون سوم این ژن انجام شد. پس از تعیین چند شکلی فضاییتکرشتهاي، محصولات PCR ،الگوهاي باندي مربوط به ژن لپتین با استفاده از ژل آکریل آمید و رنگ آمیزي نیترات،A/B/F ،A/B/E ،A/B/C ،A/C ،A/B ،C/C ،A/A الگوي 10 ،مطالعه مورد نمونهي در لپتین ژن براي. آمد بدست، نقرهF/C/A ،E/D/B/A وF/C/B/A بدست آمد که نشان دهندهي چندشکلی بالاي در ژن لپتین گوسفندان نژاد کرمانی می-باشد