So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

Human biochemical genetics

A reviewer for the Journal of the Royal Statistical Society of England comments \"This is the first book covering in one volume all important topics in genetical statistics.\" Written to provide basic probability ideas in terms of genetic situations, since the theory of genetics is a probability theory; to give a definitive treatment of applications of these ideas to genetic theory; and to describe statistical methods appropriate to the data models that are developed.

An Introduction to Genetic Statistics

The aromatic rice represents a smaller but independent rice collection, the quality of which is considered to be highly acceptable. Farmers are interested in growing aromatic rice due to high premium market price. The prime objective of this study was to enhance genetic improvement of aromatic rice. Combining ability analysis (GCA and SCA) and gene action are studied in a set of 7 × 7 half-diallel crosses. Twenty-one hybrids along with their seven parents were assessed in randomized complete block design. Different quantitative characters were used to estimate the magnitude of heterosis. GCA and SCA significance for all traits revealed the importance of both additive and nonadditive genetic components. Several genes determine quantitative traits, with each gene having very little impacts and being easily influenced by environmental factors. Pusa Basmati-1 and Govindobhog were the best combiners among the seven parents. In terms of per se performance, heterosis, and SCA effects on seed yield per plant and important yield qualities, the crosses BM-24 Deharadun Pahari, Baskota × Tulaipanji, and Pusa Basmati-1 × Tulaipanji may be of interest. Because of its interconnected processing properties, ANN can play a critical role in this experiment. As a result, the current study was carried out to collect data and validate it using an artificial neural network (ANN) on the combining ability, gene action, and heterosis involved in the expression of diverse fragrant rice features. Using ANN, the validation of the result was done and it was found that the overall efficiency was approximately 99%.

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Understanding Gene Action, Combining Ability, and Heterosis to Identify Superior Aromatic Rice Hybrids Using Artificial Neural Network

Multivariate analysis for yield and yield-related traits of amaranth genotypes from Ethiopia

Abstract Amaranths are dicotyledonous plants with high yield potential, a high mineral uptake rate, short days, and high adaptability. It has been extensively investigated as a model C4 plant. The objectives of the current study were to estimate genetic diversity, heritability, and genetic advance for yield and yield-contributing traits of amaranth genotypes based on agro-morphological traits. The study was done on one hundred twenty amaranth genotypes planted over two growing seasons using an alpha lattice design with two replications. The analysis of variance showed the presence of significant variation (P ≤ 0.001) between genotypes, years, and their interactions for most of the studied traits. Among the genotypes, based on their performance, promising genotypes KAZ-059, 225713, KAZ-058 and KEN-019, 242530, and 212890 exhibited higher leaf area, branch number, and plant height at maturity, and plant height at flowering. Selection based on these traits could be effective for amaranth leaf yield improvement. On the other hand, KEN-016, KEN-020, KAZ-060, KEN-010, KEN-018, and 22571 produced high grain yield along with better leaf area, axillary inflorescence length, terminal inflorescence lateral length, terminal inflorescence stalk length, grain sink filling rate, and thousand seed weight, indicating phenotypic-based selection on these traits might be reliable for grain yield improvement in amaranth genotypes. These genotypes were chosen as a result due to their high yield potential and good yield-related traits. Future selection efforts for amaranth should therefore continue to evaluate the genotypes under various environmental conditions. These genotypes were selected as a result because they had a high potential for yield and desirable traits that might boost yield. 

/pdf/morphological-characterization-variability-and-diversity-197bk72n.pdf

Morphological Characterization, Variability, and Diversity among Amaranth Genotypes from Ethiopia

Salinity is a major abiotic constrain faced by farmers in most rice cultivating areas of the world and improving grain yield in rice is the most important breeding objective. Twenty seven hybrids were generated in a line x tester mating design and were evaluated with their parents in a Randomized Complete Block Design at the Fadama site of the Federal University of Agriculture, Abeokuta (FUNAAB) during the 2014/2015 and 2015/2016 cropping season. Analysis of variance revealed a highly significant difference (P<0.01) among testers and lines for all traits except panicle length and a number of effective tillers per plant, respectively. Variances of Specific Combining Ability (SCA) were higher in magnitude than the corresponding General Combining Ability (GCA). The lines FARO 60 (P 7 ), OG300315 (P 10 ), NERICA L53 (P 4 ) including a tester ITA 212 (P 1 ) were the best general combiners for yield per plant. POKKALI (P 3 ) was the best general combiner for reduced vegetative growth and ITA 212 (P 1 ) and ITA 222 (P 2 ) were the best general combiners for plant height. The best specific combiner for yield per plant was P 1 x P 4 . P 3 x P 11 was the best specific combiner for reduced duration characters and P 2 x P 7 was the best specific combiner for plant height.  Estimates of narrow sense heritability (0.00 – 0.03) for all the traits under study were low which indicated preponderance of non-additive gene action governing these traits. Therefore, inter-mating among selected segregants followed by recombination breeding in an advanced generation might be advocated for improvement of the studied traits under salinity.

/pdf/combining-ability-analysis-and-gene-action-for-yield-and-2wvgs17uxs.pdf

Combining ability analysis and gene action for yield and yield related traits in rice (Oryza sativa L.) under saline conditions

Grain Amaranths are important nutritional vegetables in the world for their grains and leaves. Twelve grain Amaranth accessions were evaluated for their performances using randomized complete block design with 3 replications for 2 years to measure variability and group the accessions. Analysis of Variance and accessions performances revealed significant variability among the grain Amaranths. Phenotypic variances were higher in magnitude than genotypic variance for all the traits studied. High genetic advance was obtained for all the characters except 1000 grain weight (23.61). The genotypic coefficients of variations were lower than the phenotypic coefficient of variations. Heritability ranged from 41.08% for grain yield/plot to 62.18% for plant height at flowering. Grain yield was positive and highly significantly correlated with 1000 grain weight, leaf area but significantly correlated with leaf length and leaf width. The PCA revealed four main components of variations representing 78.06% of the total variability among the 12 grain amaranth accessions. The PCA identified all the 12 traits as strongly correlated with the three principal components. PC1 is well-correlated with Plant height at flowering, Stem girth, Number of leaves, Plant height at maturity, leaf width, leaf length, leaf area and Petiole length. The bi-plot analysis classified the accession NG/AA/03/11/010, NGB 01259, and NGB 0127 as having good leaf yield and desired leaf traits, Accession NHGB/09/108, NG/AO/08/04 and NGB 01261 were grouped as better grain yield with good yield attributes, while accession NGB 01234, NHGB 09/09 and NHAC3 are good dual purpose accessions having good grain and leaf yield.

https://ejar.journals.ekb.eg/article_174732_427b02cae71b4c9f5a17c7160c6cb19f.pdf

Francis Showemimo

Papers

Combining ability analysis and gene action for yield and yield related traits in rice (Oryza sativa L.) under saline conditions

Traits selection criteria for genetic improvement of grain and leafy Amaranth (Amaranthus spp) using Principal Component Analysis