Vallejo-Trujillo, A.R.
(2021)
Genetic diversity and adaptation to environmental challenges of Ethiopian indigenous chicken.
PhD thesis, University of Nottingham.
Abstract
Indigenous livestock species are characterized as being locally adapted, displaying low productivity but high levels of genetic diversity. They are usually resistant to diseases and suit smallholder farmers’ needs in harsh environments; hence, they represent an important resource for achieving food security in developing countries. Understanding the genetic basis of their environmental adaptations has important implications for the design of breeding improvement programs. Likewise, it may guide conservation initiatives aiming to preserve their unique adaptive diversity. Both are equally important in the current climate change scenarios challenging agricultural production systems and threatening livestock diversity.
Under variable tropical ecologies and scavenging conditions, Ethiopian indigenous chickens exhibit unique adaptations to their environments. However, little is known about the genetic mechanisms of these environmental adaptations with, so far, no in-depth analysis of the agroclimatic adaptive stressors.
Here, an innovative approach - that integrates Ecological Niche Modelling (ENM) and genome analyses (signatures of positive selection and genomic-environmental association analyses) – is applied (i) to dissect Ethiopian chicken agro-ecologies leading to the identification of the key environmental stressors, (ii) to identify and to define Ethiopian chicken ecotypes, and (iii) to identify the genetic responses to key environmental stressors.
After a brief explanation of the research context in Chapter 1 (Setting the scene), the thesis includes four results chapters.
Chapter 2 reports the diversity and population structure of the studied populations. Using Galgal_6.0 (GRCg6a) as the reference genome, 243 whole-genome sequences were analysed from Ethiopian indigenous village chickens belonging to 25 populations from diverse agro-climatic zones representing wide ecological conditions. About 19.6 million SNPs were characterized in the populations of which 29% (n = 5.6 million) were novel. While significant genetic variations are observed within the studied populations, little genetic differentiation was observed among the populations based on Fst, PCA, and admixture analyses. Population structure analyses show two major groups and several subgroups in the PCA plot, whereas three ancestral gene pools are revealed by admixture. The two main groups in the structure of the populations may likely reflect two temporally distinct migration paths of chicken into the African continent (Egypt and the East African coast). In comparison, the three ancestral genetic backgrounds can reflect these two migration routes and an additional third genetic background that remains unknown.
Before dissecting the genomic patterns of adaptation, the environmental characterization of the studied populations was performed in Chapter 3. By following an Ecological Niche Modelling approach, we identified six agro-climatic variables from an initial set of 34 as important predictors of the chicken habitats. These key predictors include one temperature variable (correlated to elevation), three precipitation variables (related to water availability), and two soil/land variables (linked to food availability). Twelve chicken ecotypes were proposed by characterizing the population habitats based on these six key environmental stressors.
Genomic signatures of environmental adaptation were then investigated in Chapter 4 and Chapter 5.
In Chapter 4, populations were ranked accordingly to the six key agro-climatic variables identified in Chapter 3. Signatures of positive selection for each extreme population pair (highest and lowest values for each environmental parameter) were investigated using Fst and XP-EHH methods. Strong candidate selected regions identified overlapping genes that have highly relevant functions for adaptation to high-altitude stresses (e.g. hypoxia, thrombosis, and cold temperatures) (UTP18, SLC43A3, P2RX3, CLP1, YPEL4, RTN4RL2, PGR2/3), high temperature (TOGARAM1), water scarcity (MANEA, HTR2C, EPHA7), and food availability under scavenging conditions (THSD4, HBE1).
In Chapter 5, genome-environmental association analysis was dissected within the 12 Ethiopian chicken ecotypes identified in Chapter 3. Within-ecotypes selection signature analyses were first performed by applying the Hp and iHS methods. This was followed by a multivariate Redundancy Analysis (RDA) to identify genomic marker outliers overlapping the sweep regions. A total of 616 outlier SNPs were identified. Only variants with environmental correlation ~ 0.3 were retained for further investigation. Candidate genes included some with functions related to thermotolerance (LDLRAD3, TNIP2, GPX7), immune response (PTPRZ1), and feed metabolisms (GPCPD1, NHLRC2, TSHD7B).
Overall, this PhD research exemplifies the use of ENM for dissecting environmental adaptation in indigenous chicken populations. It demonstrates that ENM integrated with genome-environmental association analyses is a powerful tool for studying environmental adaptation in livestock species. The outlined methodology identified several key environmental stressors allowing subsequently to investigate the genomic responses to natural selection. Moreover, the ENM based environmental characterization of the chicken habitats represents an innovative approach for livestock ecotypes identification with potential major applications for conservation and sustainable breeding improvement.
Actions (Archive Staff Only)
 |
Edit View |
Tools
Tools
