Typology, genetic diversity and genome wide scan for signatures of selection of productivity traits in indigenous goats in the Democratic Republic of Congo

Genetic characterization and assessment of signatures of selection in domestic animals adapted to local environments provide a large amount of knowledge and give a clear perspective on the population structure that assists in the decision-making of future breeding programs. This study aimed at characterizing the phenotypic and genetic diversity, the typology and production management, and carrying out a genome-wide assessment of signatures of selection on candidate genes of productivity traits (prolificacy, disease resistance and adaptability) in three Congolese indigenous goat populations (small goat, Kasai goat, and dwarf goat) across three agro-ecological zones (AEZs) in the Democratic Republic of Congo (DRC). The three AEZ regions: Kinshasa (in the stratified savannah plateau), South Kivu (in the high altitude volcanic mountains) and Tshopo (in the equatorial forest), were selected based on their accessibility and the socio-economic importance of goats. Using a structured questionnaire, information on production management, the economic benefit of keeping goats, and reproductive performance (focused on litter size) was collected from 202 farms from where phenotypic measurements were recorded for 320 adult females. From each of the 320 sample animals, five to ten (5-10) ml of total blood was collected for DNA analysis. Total genomic DNA (gDNA) was used for mtDNA d-loop region sequencing and genotyping carried out using the Goat 60K SNP chip panel. The results showed that the oldest animals were 3.34 ±1.48 years old found in South Kivu with 3.85±1.71 number of kidding. Based on the hierarchical clustering on principal components analysis, the studied goat populations were clustered into three clusters well distinguished by double and triple kidding. Prolific goats were mostly represented by goats from South Kivu mostly found in cluster two (48.33%) and three (37.22%). 82.69% of goats from Tshopo were clustered into cluster one characterized by goats with low reproductive performances (less double and triple kidding frequencies). The Canonical Discriminate Analysis (CDA) revealed that the body measurements, particularly the body length were an important variable both to discriminate and to classify goats from the three geographical regions. The Mahalanobis‘s distances revealed that indigenous goats from Kinshasa and South Kivu were not genetically distant while the largest genetic distance was observed between goats from Kinshasa and Tshopo or South Kivu and Tshopo (F-stat, p< 0.001). No improvement techniques in feeding, disease control, and reproduction management were applied in goat breeding in DRC. However, goats were considered as a source of income and saving method in smallholder farmer‘s households. The adaptability of goat to the region, disease resistance, and prolificacy were the farmer-preferred traits in the selection of goats. The analysis of 339 mitochondrial DNA displacement loop (mtDNA d-loop) sequences with a total length of 1,169 base pairs (bp) revealed a total of 568 segregating sites, resulting in 192 haplotypes. Only 9 of the 192 haplotypes were shared between the Congolese goats and goats from Kenya, Ethiopia, Algeria (1 haplotype), Zimbabwe (1 haplotype), Pakistan (1 haplotype), Cameroon (3 haplotypes), and Mozambique (3 haplotypes). Average haplotype diversity (Hd), nucleotide diversity ( ), and average number of nucleotide differences (K) were 0.987, 0.015 and 14.74, respectively. The analyses of molecular variance (AMOVA) revealed that 5.88 % of Congolese goat populations‘ variation was observed among the population and 94.12% within the population. A weak genetic differentiation was revealed between the three Congolese indigenous goat populations based on the population pairwise analysis (FST). Neighbor-joining (NJ) and Median Joining (MJ) analyses revealed both the three studied Congolese indigenous goat populations to belong to the haplogroup A with one maternal origin as revealed by the mismatch distribution analysis. Negative and significant (pvalue < 0.05) values for Fu‘s Fs (-20.418) and Tajima‘s (-2.189) tests showed that the three Congolese indigenous goat populations have expended in history. The Approximate Bayesian Computation (ABC) analyses indicated that the Congolese goats operated from the northern Africa before reach Central Africa, 354 generations in later times (~1,062years ago). Specific putative signatures of selection were identified in the three Congolese indigenous goat populations using the cross-population expended haplotype homozygosity (XP-EHH) statistical method applied across Congolese and other (Cameroon and Keffa in Ethiopia) goat populations. Positive genomic regions were enriched and annotated using the Capra hircus Genome Data Viewer Assembly ARS1 (GCF_001704415.1) and the web-based tool, Database for Annotation, Visualization, and Integrated Discovery (DAVID) software, respectively. Ten out of forty three positive genomic regions were enriched with genes involved in signalling pathways associated directly or indirectly with body size (DEPTOR, MAGEL2), behaviour and nervous systems (DCDC2, PANK3, ITSN1, COL6A3, ENPP2), prolificacy (CMK4), disease control such as a decrease in salmonella proliferation (EIF3J) and hair colour measurement, hair measurement and hair colour (PADI2). The results of this study suggest a high phenotypic and genetic diversity in Congolese indigenous goat populations clustered into three clusters well distinguished by the reproductive performances (double and triple kidding). Adaptability in the region, disease resistance and prolificacy were the major farmer-preferred traits for selecting goats to raise. A weak genetic differentiation and a single maternal origin were observed for the studied goats that underwent an expansion in the history. Novel insights into the genetic and physiological architecture of goat‘s adaptation and reproduction were revealed by the gene ontology (GO) enrichment of the positive selection regions. However, similar to the relatively poor annotation of the caprine genome, information provided by the GO analysis is limited. Since most of these candidate genes have been previously reported to be under positive selection for several traits in other species; further research should be conducted on the candidate genes reported in this study to clarify their implication and association with the reported and unreported traits in goats in DRC. These results could have implications for managing improvement strategies and long-term conservation of Congolese indigenous goats.