Evaluation framework of community-based livestock breeding programs

The objective of this paper is to present an evaluation framework to provide guidance for an assessment of the performance, outputs and associated impacts of community-based livestock breeding programs (CBBPs), responding to the need of formalizing the evaluation procedures as it was stressed by FAO. The purpose of such evaluation is to monitor and evaluate on-going activities in CBBPs, to identify challenges and mistakes in the execution of the program, so that appropriate actions can be taken. This evaluation also serves as a guide for funding bodies to measure socio-economic impact on the livelihoods of livestock farmers in order to decide if the program’s goals have been met. The evaluation framework is divided into three domains: evaluation of CBBP implementation based on organizational and technical criteria; monitoring of implementation outputs to evaluate genetic improvement at herd/flock level and the consequential changes at the household level and the community at large; and evaluation of impacts to assess improvement in livelihoods of livestock farmers and eventual effects on the environment. For each evaluation criteria, several indicators are provided.EEA BarilocheFil: Lamuno, Doreen. National Animal Genetic Resources Centre and Databank; UgandaFil: Sölkner, Johann. National Animal Genetic Resources Centre and Databank; UgandaFil: Mészáros, Gabor. National Animal Genetic Resources Centre and Databank; UgandaFil: Nakimbugwe, Helen. National Animal Genetic Resources Centre and Databank; UgandaFil: Mulindwa, Henry. National Agricultural Research Organization, UgandaFil: Nandolo, Wilson. Lilongwe University of Agriculture and Natural Resources, MalawiFil: Gondwe, Timothy. United States Department of Agriculture; Estados UnidosFil: van Tassel, Curt. United States Department of Agriculture; Estados UnidosFil: Mueller, Joaquín Pablo. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; ArgentinaFil: Wursinger, Maria. University of Natural Resources and Life Sciences; AustriaFil: Gutierrez, Gustavo. Universidad Nacional Agraria La Molina; Per

De novo assembly of the cattle reference genome with single-molecule sequencing.

BackgroundMajor advances in selection progress for cattle have been made following the introduction of genomic tools over the past 10-12 years. These tools depend upon the Bos taurus reference genome (UMD3.1.1), which was created using now-outdated technologies and is hindered by a variety of deficiencies and inaccuracies.ResultsWe present the new reference genome for cattle, ARS-UCD1.2, based on the same animal as the original to facilitate transfer and interpretation of results obtained from the earlier version, but applying a combination of modern technologies in a de novo assembly to increase continuity, accuracy, and completeness. The assembly includes 2.7 Gb and is >250× more continuous than the original assembly, with contig N50 >25 Mb and L50 of 32. We also greatly expanded supporting RNA-based data for annotation that identifies 30,396 total genes (21,039 protein coding). The new reference assembly is accessible in annotated form for public use.ConclusionsWe demonstrate that improved continuity of assembled sequence warrants the adoption of ARS-UCD1.2 as the new cattle reference genome and that increased assembly accuracy will benefit future research on this species

Using the community-based breeding program (CBBP) model as a collaborative platform to develop the African Goat Improvement Network—Image collection protocol (AGIN-ICP) with mobile technology for data collection and management of livestock phenotypes

Introduction: The African Goat Improvement Network Image Collection Protocol (AGIN-ICP) is an accessible, easy to use, low-cost procedure to collect phenotypic data via digital images. The AGIN-ICP collects images to extract several phenotype measures including health status indicators (anemia status, age, and weight), body measurements, shapes, and coat color and pattern, from digital images taken with standard digital cameras or mobile devices. This strategy is to quickly survey, record, assess, analyze, and store these data for use in a wide variety of production and sampling conditions.Methods: The work was accomplished as part of the multinational African Goat Improvement Network (AGIN) collaborative and is presented here as a case study in the AGIN collaboration model and working directly with community-based breeding programs (CBBP). It was iteratively developed and tested over 3 years, in 12 countries with over 12,000 images taken.Results and discussion: The AGIN-ICP development is described, and field implementation and the quality of the resulting images for use in image analysis and phenotypic data extraction are iteratively assessed. Digital body measures were validated using the PreciseEdge Image Segmentation Algorithm (PE-ISA) and software showing strong manual to digital body measure Pearson correlation coefficients of height, length, and girth measures (0.931, 0.943, 0.893) respectively. It is critical to note that while none of the very detailed tasks in the AGIN-ICP described here is difficult, every single one of them is even easier to accidentally omit, and the impact of such a mistake could render a sample image, a sampling day’s images, or even an entire sampling trip’s images difficult or unusable for extracting digital phenotypes. Coupled with tissue sampling and genomic testing, it may be useful in the effort to identify and conserve important animal genetic resources and in CBBP genetic improvement programs by providing reliably measured phenotypes with modest cost. Potential users include farmers, animal husbandry officials, veterinarians, regional government or other public health officials, researchers, and others. Based on these results, a final AGIN-ICP is presented, optimizing the costs, ease, and speed of field implementation of the collection method without compromising the quality of the image data collection

Estimation of inbreeding in Ethiopia goats using runs of homozygosity

This study was carried out to estimate the inbreeding levels in Abergelle, Gumuz, Keffa and Woytoguji goats in Ethiopia from genomic information. A total of 161 animals (53 Abergelle, 39 Gumuz, 31 Keffa and 38 Woytoguji) were genotyped using the Illumina 50K SNP chip. Runs of homozygosity were computed at cut-offs of 1MB, 2MB, 4MB, 8MB and 16MB, using cgaTOH Analysis & Clustering Suite, Version 1.0.1. The estimated levels of inbreeding based on runs of homozygosity greater than 1MB were 0.0210, 0.0209, 0.0502 and 0.0199 for Abergelle, Gumuz, Keffa and Woytoguji, respectively. The results suggest that inbreeding levels are low in the four breeds, although relatively higher in the Keffa breed than in the other three breeds. Suitable strategies may need to be implemented for reducing inbreeding when designing breeding programmes for the Keffa goats

Experiences from the Implementation of Community-Based Goat Breeding Programs in Malawi and Uganda: A Potential Approach for Conservation and Improvement of Indigenous Small Ruminants in Smallholder Farms

Maintaining diversity of small ruminant genetic resources is instrumental for sustainable agricultural production. Community-based livestock breeding programs (CBBPs) have emerged as a potential approach to implement breeding programs in smallholder farms. This study assesses the viability of CBBPs as a potential approach for conservation and improvement of indigenous small ruminants, using case studies of goat CBBPs in Malawi and Uganda. Data were collected using focus group discussions, personal interviews, and direct observations. The program promotes and empowers smallholders to have access to small ruminant feed resources through protection of existing communal pasturelands, capacity building in pasture production, and conservation of crop residues and crop by-products. Implementation of the CBBP enhances the contributions through improved animal growth performance, kids’ survival, and twinning rates leading to increased offtake rates and better prices. The existence of permanently established supporting organizations and other stakeholders provides sustainable institutional support instrumental for the establishment and growth of CBBPs. However, establishment of functional community-based institutions (producer cooperatives) and investments in institutional/policy reforms to safeguard fair trading, access to common resources by small ruminant keepers, and adoption of the CBBP model into national livestock development programs are some of the key milestones that can guarantee sustainability

Genome-wide association study for the level of prolificacy in Cameroon’s native goat

ABSTRACTIncome from goats highly depends on prolificacy, which is difficult to improve by traditional breeding methods. The study aimed to identify SNP markers for prolificacy, using a case–control genome-wide association study (GWAS) on 111 genotyped Cameroon native goat (CNG) does, based on the 50 K single nucleotide polymorphism (SNP) chip panel. None of the top SNPs reached the significant p-value of 5 × 10−8. The highest p-value was 0.0009. Despite the number of cases being about a quarter of the number of controls, the highest allele frequency of some of the top 20 variants in the cases was indicative of their potential role in the trait. These top variants included the following 15: rs268285661, rs268235169, rs268236449, rs268235135, rs268240394 in Sphingosine-1-phosphate phosphatase 2 (SGPP2) gene, rs268283635 in Solute carrier family 24 member 2 (SLC24A2) gene, rs268251678 in Androgen-induced gene 1 (AIG1) gene, rs268267018, rs268239617, rs268281364, rs268273029, rs268286941, rs268236144, rs268233233 in CEP126 gene and rs268278159, respectively. Our findings indicate that GWAS enable the identification of some loci within genes, with known biological functions and pathways in human being and mice animal model but far-ranging to what was previously hypothesized and tested in goat

Genome-wide association study for the level of prolificacy in Cameroon’s native goat

Income from goats highly depends on prolificacy, which is difficult to improve by traditional breeding methods. The study aimed to identify SNP markers for prolificacy, using a case–control genome-wide association study (GWAS) on 111 genotyped Cameroon native goat (CNG) does, based on the 50 K single nucleotide polymorphism (SNP) chip panel. None of the top SNPs reached the significant p-value of 5 × 10−8. The highest p-value was 0.0009. Despite the number of cases being about a quarter of the number of controls, the highest allele frequency of some of the top 20 variants in the cases was indicative of their potential role in the trait. These top variants included the following 15: rs268285661, rs268235169, rs268236449, rs268235135, rs268240394 in Sphingosine-1-phosphate phosphatase 2 (SGPP2) gene, rs268283635 in Solute carrier family 24 member 2 (SLC24A2) gene, rs268251678 in Androgen-induced gene 1 (AIG1) gene, rs268267018, rs268239617, rs268281364, rs268273029, rs268286941, rs268236144, rs268233233 in CEP126 gene and rs268278159, respectively. Our findings indicate that GWAS enable the identification of some loci within genes, with known biological functions and pathways in human being and mice animal model but far-ranging to what was previously hypothesized and tested in goat.</p

Misidentification of runs of homozygosity islands in cattle caused by interference with copy number variation or large intermarker distances

International audienceAbstractBackgroundRuns of homozygosity (ROH) islands are stretches of homozygous sequence in the genome of a large proportion of individuals in a population. Algorithms for the detection of ROH depend on the similarity of haplotypes. Coverage gaps and copy number variants (CNV) may result in incorrect identification of such similarity, leading to the detection of ROH islands where none exists. Misidentified hemizygous regions will also appear as homozygous based on sequence variation alone. Our aim was to identify ROH islands influenced by marker coverage gaps or CNV, using Illumina BovineHD BeadChip (777 K) single nucleotide polymorphism (SNP) data for Austrian Brown Swiss, Tyrol Grey and Pinzgauer cattle.MethodsROH were detected using clustering, and ROH islands were determined from population inbreeding levels for each marker. CNV were detected using a multivariate copy number analysis method and a hidden Markov model. SNP coverage gaps were defined as genomic regions with intermarker distances on average longer than 9.24 kb. ROH islands that overlapped CNV regions (CNVR) or SNP coverage gaps were considered as potential artefacts. Permutation tests were used to determine if overlaps between CNVR with copy losses and ROH islands were due to chance. Diversity of the haplotypes in the ROH islands was assessed by haplotype analyses.ResultsIn Brown Swiss, Tyrol Grey and Pinzgauer, we identified 13, 22, and 24 ROH islands covering 26.6, 389.0 and 35.8 Mb, respectively, and we detected 30, 50 and 71 CNVR derived from CNV by using both algorithms, respectively. Overlaps between ROH islands, CNVR or coverage gaps occurred for 7, 14 and 16 ROH islands, respectively. About 37, 44 and 52% of the ROH islands coverage in Brown Swiss, Tyrol Grey and Pinzgauer, respectively, were affected by copy loss. Intersections between ROH islands and CNVR were small, but significantly larger compared to ROH islands at random locations across the genome, implying an association between ROH islands and CNVR. Haplotype diversity for reliable ROH islands was lower than for ROH islands that intersected with copy loss CNVR.ConclusionsOur findings show that a significant proportion of the ROH islands in the bovine genome are artefacts due to CNV or SNP coverage gaps

The African Goat Improvement Network: a scientific group empowering smallholder farmers

The African Goat Improvement Network (AGIN) is a collaborative group of scientists focused on genetic improvement of goats in small holder communities across the African continent. The group emerged from a series of workshops focused on enhancing goat productivity and sustainability. Discussions began in 2011 at the inaugural workshop held in Nairobi, Kenya. The goals of this diverse group were to: improve indigenous goat production in Africa; characterize existing goat populations and to facilitate germplasm preservation where appropriate; and to genomic approaches to better understand adaptation. The long-term goal was to develop cost-effective strategies to apply genomics to improve productivity of small holder farmers without sacrificing adaptation. Genome-wide information on genetic variation enabled genetic diversity studies, facilitated improved germplasm preservation decisions, and provided information necessary to initiate large scale genetic improvement programs. These improvements were partially implemented through a series of community-based breeding programs that engaged and empowered local small farmers, especially women, to promote sustainability of the production system. As with many international collaborative efforts, the AGIN work serves as a platform for human capacity development. This paper chronicles the evolution of the collaborative approach leading to the current AGIN organization and describes how it builds capacity for sustained research and development long after the initial program funds are gone. It is unique in its effectiveness for simultaneous, multi-level capacity building for researchers, students, farmers and communities, and local and regional government officials. The positive impact of AGIN capacity building has been felt by participants from developing, as well as developed country partners

De novo assembly of the cattle reference genome with single-molecule sequencing.

Major advances in selection progress for cattle have been made following the introduction of genomic tools over the past 10-12 years. These tools depend upon the Bos taurus reference genome (UMD3.1.1), which was created using now-outdated technologies and is hindered by a variety of deficiencies and inaccuracies. We present the new reference genome for cattle, ARS-UCD1.2, based on the same animal as the original to facilitate transfer and interpretation of results obtained from the earlier version, but applying a combination of modern technologies in a de novo assembly to increase continuity, accuracy, and completeness. The assembly includes 2.7 Gb and is &gt;250× more continuous than the original assembly, with contig N50 &gt;25 Mb and L50 of 32. We also greatly expanded supporting RNA-based data for annotation that identifies 30,396 total genes (21,039 protein coding). The new reference assembly is accessible in annotated form for public use. We demonstrate that improved continuity of assembled sequence warrants the adoption of ARS-UCD1.2 as the new cattle reference genome and that increased assembly accuracy will benefit future research on this species