Application of factor analytic and spatial mixed models for the analysis of multi-environment trials in common bean (Phaseolus vulgaris L.) in Ethiopia.

Common bean (Phaseolus vulgaris L.) is one of the most important grain legumes consumed globally, especially in Ethiopia, for its edible seeds, cash crops, and supply of protein for farmers. Efficient statistical methods must be employed for the evaluation of common bean varieties to accurately select superior varieties that contribute to agricultural productivity. The objective of this study was to identify promising large mottled bean varieties through analysis of multi-environment trials (MET) data using multiplicative spatial mixed models. In this study, 16-18 large mottled common bean varieties, including one check, were sown across nine growing environments in Ethiopia using lattice and alpha lattice designs, with three replications laid out in a square or rectangular (row by column) array of plots, respectively during the main cropping season from 2015 to 2018. We present a linear mixed model analysis that integrates spatial and factor analytic (FA) models, and the heritability measure was used to evaluate the efficiency of these models with the conventional analysis. The analysis of the spatial model, and more significantly, the spatial+FA model, revealed a notable enhancement in heritability. With the exception of a trial conducted at Kobo, a genotype DAP 292, found to be good performing for days to flowering and maturity, but for yield only across four clusters of trials, C2, C3, C5 and C7, formed with trials of relatively high genetic variance. Across these clusters, the yield advantage of this variety over the check ranged from 10-32%. This genotype also has a yield that is somewhat comparable to the check across the remaining clusters. Overall, both the spatial and factor analytic models proved to be effective approaches for analyzing the data in this study. The analysis of multi-environment trial data through the use of more efficient statistical models can provide a more robust platform for evaluating common bean varieties with greater confidence in selecting superior varieties across a range of environments. Hence, scaling up the use of this efficient analysis method is indispensable for enhancing the selection of superior varieties.

Evaluation of finger millet (Eleusine coracana (L.) Gaertn.) in multi-environment trials using enhanced statistical models.

Spatial variation and genotype by environment (GxE) interaction are common in varietal selection field trials and pose a significant challenge for plant breeders when comparing the genetic potential of different varieties. Efficient statistical methods must be employed for the evaluation of finger millet breeding trials to accurately select superior varieties that contribute to agricultural productivity. The objective of this study was to improve selection strategies in finger millet breeding in Ethiopia through modeling of spatial field trends and the GxE interaction. A dataset of seven multi-environment trials (MET) conducted in randomized complete block design (RCBD) with two replications laid out in rectangle (row x column) arrays of plots was used in this study. The results revealed that, under the linear mixed model, the spatial and factor analytic (FA) models were efficient methods of data analysis for this study, and this was demonstrated with evidence of heritability measure. We found two clusters of correlated environments that helped to select superior and stable varieties through ranking average Best Linear Unbiased Predictors (BLUPs) within clusters. The first cluster was chosen because it contained a greater number of environments with high heritability. Based on this cluster, Bako-09, 203439, 203325, and 203347 were the top four varieties with relatively high yield performance and stability across correlated environments. Hence, scaling up the use of this efficient analysis method will improve the selection of superior finger millet varieties.

Genetic diversity of DGAT1 gene linked to milk production in cattle populations of Ethiopia.

BACKGROUND: Diacylglycerol acyl-CoA acyltransferase 1 (DGAT1) has become a promising candidate gene for milk production traits because of its important role as a key enzyme in catalyzing the final step of triglyceride synthesis. Thus use of bovine DGAT1 gene as milk production markers in cattle is well established. However, there is no report on polymorphism of the DGAT1 gene in Ethiopian cattle breeds. The present study is the first comprehensive report on diversity, evolution, neutrality evaluation and genetic differentiation of DGAT1 gene in Ethiopian cattle population. The aim of this study was to characterize the genetic variability of exon 8 region of DGAT1 gene in Ethiopian cattle breeds. RESULTS: Analysis of the level of genetic variability at the population and sequence levels with genetic distance in the breeds considered revealed that studied breeds had 11, 0.615 and 0.010 haplotypes, haplotype diversity and nucleotide diversity respectively. Boran-Holstein showed low minor allele frequency and heterozygosity, while Horro showed low nucleotide and haplotype diversities. The studied cattle DGAT1 genes were under purifying selection. The neutrality test statistics in most populations were negative and statistically non-significant (p > 0.10) and consistent with a populations in genetic equilibrium or in expansion. Analysis for heterozygosity, polymorphic information content and inbreeding coefficient revealed sufficient genetic variation in DGAT1 gene. The pairwise FST values indicated significant differentiation among all the breeds (FST = 0.13; p ≤ 0.05), besides the rooting from the evolutionary or domestication history of the cattle inferred from the phylogenetic tree based on the neighbourhood joining method. There was four separated cluster among the studied cattle breeds, and they shared a common node from the constructed tree. CONCLUSION: The cattle populations studied were polymorphic for DGAT1 locus. The DGAT1 gene locus is extremely crucial and may provide baseline information for in-depth understanding, exploitation of milk gene variation and could be used as a marker in selection programmes to enhance the production potential and to accelerate the rate of genetic gain in Ethiopian cattle populations exposed to different agro ecology condition.

Genetic diversity, population structure and relationship of Ethiopian barley (Hordeum vulgare L.) landraces as revealed by SSR markers.

Evaluation and characterization of genetic resources maintained at both in situ and ex situ GenBanks have important implications for future utilization in association mapping studies, genetic selection, breeding and conservation activities. The main objective of this study was to evaluate the genetic diversity, population structure and relationship of 384 Ethiopian barley genotypes collected from different barley growing regions of Ethiopia using 49 simple sequence repeat (SSR) markers. Analysis of these 49 SSR markers amplified a total of 478 alleles with an average of 9.755 alleles per locus were obtained of which 97.07% of the loci were observed to be polymorphic. Nei's genetic diversity index (h) was 0.654 and the Shannon diversity index (I) was 0.647, indicating that the genetic diversity in barley genotypes studied was moderately high. At the population level, mean per cent of polymorphic loci (PPL) showed 98.37%, h = 0.388 and I = 0.568. Highest level of genetic diversity was observed in the Arsi population (with PPL = 100%, h = 0.439, I = 0.624); the lowest value observed was in population from Jimma (with PPL = 75.51%, h = 0.291, I = 0.430). Analysis of molecular variance (AMOVA) result showed significant genetic differentiation within and between populations (P<0.001), with 84.21% and 15.79% of the variation occurring within and among populations, respectively. Further, genetic variation analysis showed a coefficient of gene differentiation of 0.053 and a gene flow value of 4.467 among populations. The 384 barley genotypes were divided into seven genetic clusters according to STRUCTURE, neighbour-joining tree and principal coordinate analysis, correlating significantly with geographic distribution. These results signified presence of significant variations within and among populations (P<0.001), with the highest of the variation occurring within populations. The results will also assist with the design of conservation strategies, such as genetic protection via both in situ and ex situ conservation.

Genome-wide association analysis of anthracnose resistance in sorghum [Sorghum bicolor (L.) Moench].

In warm-humid ago-ecologies of the world, sorghum [Sorghum bicolor (L.) Moench] production is severely affected by anthracnose disease caused by Colletotrichum sublineolum Henn. New sources of anthracnose resistance should be identified to introgress novel genes into susceptible varieties in resistance breeding programs. The objective of this study was to determine genome-wide association of Diversity Arrays Technology Sequencing (DArTseq) based single nucleotide polymorphisms (SNP) markers and anthracnose resistance genes in diverse sorghum populations for resistance breeding. Three hundred sixty-six sorghum populations were assessed for anthracnose resistance in three seasons in western Ethiopia using artificial inoculation. Data on anthracnose severity and the relative area under the disease progress curve were computed. Furthermore, the test populations were genotyped using SNP markers with DArTseq protocol. Population structure analysis and genome-wide association mapping were undertaken based on 11,643 SNPs with <10% missing data. The evaluated population was grouped into eight distinct genetic clusters. A total of eight significant (P < 0.001) marker-trait associations (MTAs) were detected, explaining 4.86-15.9% of the phenotypic variation for anthracnose resistance. Out of which the four markers were above the cutoff point. The significant MTAs in the assessed sorghum population are useful for marker-assisted selection (MAS) in anthracnose resistance breeding programs and for gene and quantitative trait loci (QTL) mapping.

DArTSeq SNP-based markers revealed high genetic diversity and structured population in Ethiopian cowpea [Vigna unguiculata (L.) Walp] germplasms.

Cowpea [Vigna unguiculata (L.) Walp] is one of the important climate-resilient legume crops for food and nutrition security in sub-Saharan Africa. Ethiopia is believed to harbor high cowpea genetic diversity, but this has not yet been efficiently characterized and exploited in breeding. The objective of this study was to evaluate the extent and pattern of genetic diversity in 357 cowpea accestions comprising landraces (87%), breeding lines (11%) and released varieties (2%), using single nucleotide polymorphism markers. The overall gene diversity and heterozygosity were 0.28 and 0.12, respectively. The genetic diversity indices indicated substantial diversity in Ethiopian cowpea landraces. Analysis of molecular variance showed that most of the variation was within in the population (46%) and 44% between individuals, with only 10% of the variation being among populations. Model-based ancestry analysis, the phylogenetic tree, discriminant analysis of principal components and principal coordinate analysis classified the 357 genotypes into three well-differentiated genetic populations. Genotypes from the same region grouped into different clusters, while others from different regions fell into the same cluster. This indicates that differences in regions of origin may not be the main driver determining the genetic diversity in cowpea in Ethiopia. Therefore, differences in sources of origin, as currently distributed in Ethiopia, should not necessarily be used as indices of genetic diversity. Choice of parental lines should rather be based on a systematic assessment of genetic diversity in a specific population. The study also suggested 94 accesstions as core collection which retained 100% of the genetic diversity from the entire collection. This core set represents 26% of the entire collection pinpointing a wide distribution of the diversity within the ethiopian landraces. The outcome of this study provided new insights into the genetic diversity and population structure in Ethiopian cowpea genetic resources for designing effective collection and conservation strategies for efficient utilization in breeding.