Enlarging a training set for genomic selction by imputation of un-genotyped animals in populations of varying genetic architecture

Background: The most common application of imputation is to infer genotypes of a high-density panel of markers on animals that are genotyped for a low-density panel. However, the increase in accuracy of genomic predictions resulting from an increase in the number of markers tends to reach a plateau beyond a certain density. Another application of imputation is to increase the size of the training set with un-genotyped animals. This strategy can be particularly successful when a set of closely related individuals are genotyped. ----- Methods: Imputation on completely un-genotyped dams was performed using known genotypes from the sire of each dam, one offspring and the offspring’s sire. Two methods were applied based on either allele or haplotype frequencies to infer genotypes at ambiguous loci. Results of these methods and of two available software packages were compared. Quality of imputation under different population structures was assessed. The impact of using imputed dams to enlarge training sets on the accuracy of genomic predictions was evaluated for different populations, heritabilities and sizes of training sets. ----- Results: Imputation accuracy ranged from 0.52 to 0.93 depending on the population structure and the method used. The method that used allele frequencies performed better than the method based on haplotype frequencies. Accuracy of imputation was higher for populations with higher levels of linkage disequilibrium and with larger proportions of markers with more extreme allele frequencies. Inclusion of imputed dams in the training set increased the accuracy of genomic predictions. Gains in accuracy ranged from close to zero to 37.14%, depending on the simulated scenario. Generally, the larger the accuracy already obtained with the genotyped training set, the lower the increase in accuracy achieved by adding imputed dams. ----- Conclusions: Whenever a reference population resembling the family configuration considered here is available, imputation can be used to achieve an extra increase in accuracy of genomic predictions by enlarging the training set with completely un-genotyped dams. This strategy was shown to be particularly useful for populations with lower levels of linkage disequilibrium, for genomic selection on traits with low heritability, and for species or breeds for which the size of the reference population is limited.

Opportunities and constraints of peri-urban buffalo and dairy cattle systems in Faisalabad, Punjab, Pakistan

In the big cities of Pakistan, peri-urban dairy production plays an important role for household income generation and the supply of milk and meat to the urban population. On the other hand, milk production in general, and peri-urban dairy production in particular, faces numerous problems that have been well known for decades. Peri-urban dairy producers have been especially neglected by politicians as well as non-government-organizations (NGOs). Against this background, a study in Pakistan’s third largest city, Faisalabad (Punjab Province), was carried out with the aims of gathering basic information, determining major constraints and identifying options for improvements of the peri-urban milk production systems. For data collection, 145 peri-urban households (HH) engaged in dairy production were interviewed face to face using a structured and pretested questionnaire with an interpreter. For analyses, HH were classified into three wealth groups according to their own perception. Thus, 38 HH were poor, 95 HH well off and 12 HH rich (26.2%, 65.5% and 8.3%, respectively). The richer the respondents perceived their HH, the more frequently they were actually in possession of high value HH assets like phones, bank accounts, motorbikes, tractors and cars. Although there was no difference between the wealth groups with respect to the number of HH members (about 10, range: 1 to 23), the educational level of the HH heads differed significantly: on average, heads of poor HH had followed education for 3 years, compared to 6 years for well off HH and 8 years for rich HH. About 40% of the poor and well off HH also had off-farm incomes, while the percentage was much higher - two thirds (67%) - for the rich HH. The majority of the HH were landless (62%); the rest (55 HH) possessed agricultural land from 0.1 to 10.1 ha (average 2.8 ha), where they were growing green fodder: maize, sorghum and pearl millet in summer; berseem, sugar cane and wheat were grown in winter. Dairy animals accounted for about 60% of the herds; the number of dairy animals per HH ranged from 2 to 50 buffaloes (Nili-Ravi breed) and from 0 to 20 cows (mostly crossbred, also Sahiwal). About 37% (n=54) of the HH did not keep cattle. About three quarters of the dairy animals were lactating. The majority of the people taking care of the animals were family workers; 17.3% were hired labourers (exclusively male), employed by 11 rich and 32 well off HH; none of the poor HH employed workers, but the percentages were 33.7% for the well off and 91.7% for the rich HH. The total number of workers increased significantly with increasing wealth (poor: 2.0; well off:2.5; rich: 3.4). Overall, 69 female labourers were recorded, making up 16.8% of employed workers and one fourth of the HH’s own labourers. Apparently, their only duty was to clean the animals´ living areas; only one of them was also watering and showering the animals. Poor HH relied more on female workers than the other two groups: 27.1% of the workers of poor HH were women, but only 14.8% and 6.8% of the labour force of well off and rich HH were female. Two thirds (70%) of the HH sold milk to dhodis (middlemen) and one third (35%) to neighbours; three HH (2%) did doorstep delivery and one HH (1%) had its own shop. The 91 HH keeping both species usually sold mixed milk (97%). Clients for mixed and pure buffalo milk were dhodis (78%, respectively 59%) and neighbours (28%, respectively 47%). The highest milk prices per liter (Pakistani Rupees, 100 PKR @ 0.8 Euro) were paid by alternative clients (44 PKR; 4 HH), followed by neighbours (40 PKR, 50 HH); dhodis paid lower prices (36 PKR, 99 HH). Prices for pure buffalo and mixed milk did not differ significantly. However, HH obtaining the maximum price from the respective clients for the respective type of milk got between 20% (mixed milk, alternative clients) and 68% (mixed milk, dhodi) more than HH fetching the minimum price. Some HH (19%) reported 7% higher prices for the current summer than the preceding winter. Amount of milk sold and distance from the HH to the city center did not influence milk prices. Respondents usually named problems that directly affected their income and that were directly and constantly visible to them, such as high costs, little space and fodder shortages. Other constraints that are only influencing their income indirectly, e.g. the relatively low genetic potential of their animals due to neglected breeding as well as the short- and long-term health problems correlated with imbalanced feeding and insufficient health care, were rarely named. The same accounts for problems accompanying improper dung management (storage, disposal, burning instead of recycling) for the environment and human health. Most of the named problems are linked to each other and should be addressed within the context of the entire system. Therefore, further research should focus on systematic investigations and improvement options, taking a holistic and interdisciplinary approach instead of only working in single fields. Concerted efforts of dairy farmers, researchers, NGOs and political decision makers are necessary to create an economic, ecological and social framework that allows dairy production to serve the entire society. For this, different improvement options should be tested in terms of their impact on environment and income of the farmers, as well as feasibility and sustainability in the peri-urban zones of Faisalabad.

Dairy farms typology and management of animal genetic resources in the peri-urban zone of Bamako (Mali)

Facing growth in demand, dairy production in peri-urban areas of developing countries is changing rapidly. To characterise this development around Bamako (Mali), this study establishes a typology of dairy production systems with a special focus on animal genetic resources. The survey included 52 dairy cattle farms from six peri-urban sites. It was conducted in 2011 through two visits, in the dry and harvest seasons. The median cattle number per farm was 17 (range 5-118) and 42% of farmers owned cropland (8.3 +/- 7.3 ha, minimum 1 ha, maximum 25 ha). Feeding strategy was a crucial variable in farm characterisation, accounting for about 85% of total expenses. The use of artificial insemination and a regular veterinary follow-up were other important parameters. According to breeders’ answers, thirty genetic profiles were identified, from local purebreds to different levels of crossbreds. Purebred animals raised were Fulani Zebu (45.8%), Maure Zebu (9.2%), Holstein (3.0%), Azawak Zebu (1.3%), Mere Zebu (0.5%) and Kuri taurine (0.1%). Holstein crossbred represented 30.5% of the total number of animals (19.0% Fulani-Holstein, 11.2% Maure-Holstein and 0.3% Kuri-Holstein). Montbéliarde, Normande and Limousin crossbreds were also found (6.6%, 0.7% and 0.3%, respectively). A multivariate analysis helped disaggregate the diversity of management practices. The high diversity of situations shows the need for consideration of typological characteristics for an appropriate intervention. Although strongly anchored on local breeds, the peri-urban dairy systems included a diversity of exotic cattle, showing an uncoordinated quest of breeders for innovation. Without a public intervention, this dynamic will result in an irremediable erosion of indigenous animal genetic resources.