Browsing by Subject "Quantitative genetics"

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Breeding for resilient cows
(2025) Keßler, Franziska; Bennewitz, Jörn
Dairy cows are an indispensable part of modern livestock farming and make a significant contribution to human nutrition with producing a high-quality protein. At the same time, they are influenced by environmental factors and must maintain their performance, stay healthy, and remain fertile under given environmental conditions. In recent decades, we have faced an increasing number of new or suddenly emerging environmental stressors: extreme weather events, heatwaves, invasive species, and constantly changing requirements for housing conditions are just a few examples. This demands a high level of robustness and resilience from our dairy cows. While comprehensive research has been conducted on adaptation to changing environmental conditions, there is still a lack of knowledge about coping with short-term disturbances. Resilience is the ability of an individual to respond to these disturbances, recover from them, and return to its previous physiological equilibrium while maintaining the same level of performance. This study examines the concept of resilience in German dairy cattle breeds, analyzes genetic parameters, and discusses possibilities for future breeding strategies. The first chapter describes interactions between organisms and the environment, as well as statistical approaches to assessing the influence of environmental gradients on livestock. The concepts of resilience and robustness were distinguished, and methods for measuring and phenotyping resilience were explored. A promising approach is the analysis of variance and autocorrelation of daily milk yields during lactation. Under the assumption that resilient animals maintain a stable performance level along a natural lactation curve, low variance and an autocorrelation close to zero indicate high resilience. The genetic parameters of these resilience indicator traits were studied in the second chapter for the three most important German dairy breeds: German Holstein, German Fleckvieh, and German Brown Swiss. Within each breed and across breeds, low to moderate heritabilities were observed, along with desirable phenotypic and genetic correlations with performance traits. A comparison between breeds revealed only minimal differences, with no clear trend across all resilience indicator traits studied. Next, correlations between resilience indicator traits and functional as well as health traits were analyzed. While hardly any significant correlations were found for autocorrelation, the variance of daily milk yield correlated in a desirable direction with these traits. Resilient animals appear to be healthier and more long-lived. Chapter three also discusses the design of a selection index for resilience. This requires economic weighting factors, which cannot yet be determined. Therefore, optimizing the selection index resilience by maximizing breeding response in the selection index health was proposed. It was shown that breeding for resilience would lead to genetic progress in overall health. In the German Holstein breed, which was exclusively considered in this context, a selection index consisting of two different variance-based resilience indicator traits was recommended. The adaptation of the methodology to optimize a selection index to the German Fleckvieh and German Brown Swiss breeds was subsequently addressed in the general discussion and considered feasible. The fourth chapter analyzes the genetic architecture of resilience using genome-wide association studies within the three dairy breeds. The results indicated that the resilience indicator traits are polygenic traits. SNPs that significantly influence resilience are located near to QTLs known to affect performance, fertility, or health. Additionally, population structure was examined using linkage disequilibrium analysis. The final general discussion applied the methods from chapter three to the German Fleckvieh and German Brown Swiss breeds. Significant negative, undesirable correlations between autocorrelation and functional and health traits were found in German Fleckvieh. In contrast, variance-based resilience indicator traits correlated positively with most known traits, which is desirable. A selection index resilience was proposed for both breeds, consisting of two to three individual indicator traits, similar to the German Holstein breed. To better understand resilience, differences in breeding values were translated into milk loss per lactation, the number of disturbances an individual suffered from, and the impact on test-day results for milk ingredients. Finally, an outlook was provided on potential future research directions for resilience in livestock.
Comparison of omics technologies for hybrid prediction
(2019) Westhues, Matthias; Melchinger, Albrecht E.
One of the great challenges for plant breeders is dealing with the vast number of putative candidates, which cannot be tested exhaustively in multi-environment field trials. Using pedigree records helped breeders narrowing down the number of candidates substantially. With pedigree information, only a subset of candidates need to be subjected to exhaustive tests of their phenotype whereas the phenotype of the majority of untested relatives is inferred from their common pedigree. A caveat of pedigree information is its inability to capture Mendelian sampling and to accurately reflect relationships among individuals. This shortcoming was mitigated with the advent of marker assays covering regions harboring causal quantitative trait loci. Today, the prediction of untested candidates using information from genomic markers, called genomic prediction, is a routine procedure in larger plant breeding companies. Genomic prediction has revolutionized the prediction of traits with complex genetic architecture but, just as pedigree, cannot properly capture physiological epistasis, referring to complex interactions among genes and endophenotypes, such as RNA, proteins and metabolites. Given their intermediate position in the genotype-phenotype cascade, endophenotypes are expected to represent some of the information missing from the genome, thereby potentially improving predictive abilities. In a first study we explored the ability of several predictor types to forecast genetic values for complex agronomic traits recorded on maize hybrids. Pedigree and genomic information were included as the benchmark for evaluating the merit of metabolites and gene expression data in genetic value prediction. Metabolites, sampled from maize plants grown in field trials, were poor predictors for all traits. Conversely, root-metabolites, grown under controlled conditions, were moderate to competitive predictors for the traits fat as well as dry matter yield. Gene expression data outperformed other individual predictors for the prediction of genetic values for protein and the economically most relevant trait dry matter yield. A genome-wide association study suggested that gene expression data integrated SNP interactions. This might explain the superior performance of this predictor type in the prediction of protein and dry matter yield. Small RNAs were probed for their potential as predictors, given their involvement in transcriptional, post-transcriptional and post-translational regulation. Regardless of the trait, small RNAs could not outperform other predictors. Combinations of predictors did not considerably improve the predictive ability of the best single predictor for any trait but improved the stability of their performance across traits. By assigning different weights to each predictor, we evaluated each predictors optimal contribution for attaining maximum predictive ability. This approach revealed that pedigree, genomic information and gene expression data contribute equally when maximizing predictive ability for grain dry matter content. When attempting to maximize predictive ability for grain yield, pedigree information was superfluous. For genotypes having only genomic information, gene expression data were imputed by using genotypes having both, genomic as well as gene expression data. Previously, this single-step prediction framework was only used for qualitative predictors. Our study revealed that this framework can be employed for improving the cost-effectiveness of quantitative endophenotypes in hybrid prediction. We hope that these studies will further promote exploring endophenotypes as additional predictor types in breeding.
Maximization through optimization? On the relationship between hybrid performance and parental genetic distance
(2023) Würschum, Tobias; Zhu, Xintian; Zhao, Yusheng; Jiang, Yong; Reif, Jochen C.; Maurer, Hans Peter
Heterosis is the improved performance of hybrids compared with their parental components and is widely exploited in agriculture. According to quantitative genetic theory, genetic distance between parents at heterotic quantitative trait loci is required for heterosis, but how heterosis varies with genetic distance has remained elusive, despite intensive research on the topic. Experimental studies have often found a positive association between heterosis and genetic distance that, however, varied in strength. Most importantly, it has remained unclear whether heterosis increases continuously with genetic distance or whether there is an optimum genetic distance after which heterosis declines again. Here, we revisit the relationship between heterosis and genetic distance and provide perspectives on how to maximize heterosis and hybrid performance in breeding, as well as the consequences for the design of heterotic groups and the utilization of more exotic material and genetic resources.
Stirring up sorghum hybrid breeding targeting West African smallholder farmers low input environments
(2019) Kante, Papa Ndiaga Moctar; Haussmann, Bettina
Food supply and income in rural areas of West Africa (WA) depend strongly on the local production, and mostly on farmers’ field production of root and tuber crops, and cereals. To feed an ever-increasing population in a context of climate-change and low-input cultural conditions, breeding for resilient crops can guarantee smallholder farmers food security and cash income for a sustainable rural development. Sorghum hybrids for WA were first explored in the early 1970s and hybrid crosses of Malian landraces with introduced Caudatum-race seed parents were evaluated in the early 80s. Although those hybrids exhibited good heterosis for grain yield, their lack of grain quality made them commercially unsustainable. Efforts by the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) and its partners resulted in the first series of Guinea-race based hybrids. The short statured hybrids were evaluated in several on-farm farmer-managed yield trials, and showed satisfactory grain yield and quality under farmers’ cultivation conditions. Although taller- relative to shorter- height sorghum can help reduce risks of panicle loss by grazing transhumant cattle, no indication on the yield potential of the tall statured hybrids is available. The advances achieved by ICRISAT and its partners in hybrid development justified establishing a long-term hybrid breeding program to provide farmers with hybrids with sufficient grain yield and good grain quality under low input conditions. However, the lack of quantitative genetic information about the genetic value of new experimental hybrids and their parents (Guinea-Caudatum to complete Guinea background, from different WA origins), or about the efficiency of alternative selection methods for targeting yield performance in the predominantly low-input and phosphorous-deficient sorghum production conditions hinders sorghum hybrid development for this region. Sorghum hybrid breeding was commercially feasible only after the identification of a heritable and stable cytoplasmic male sterility (CMS) mechanism. Hybrid breeding in WA can benefit from molecular marker, especially for the fertility restoration/sterility maintenance of the predominant A1-type of CMS. The major outcomes of this thesis are presented as follow: Mean yields of tall hybrids were 3 to 17% (ranging from 6 to 28 g m−2) higher than that of the local check across all 37 on-farm farmer-managed environments and were highest (14–47%) averaged across the seven trials with the lowest mean yields. The yields of the new set of experimental hybrids were substantially superior to farmers’ local Guinea-race varieties, with 20 to 80% higher means over all hybrids in both low phosphorus (LP) and high phosphorus (HP) environments. Average mid-parent and better-parent heterosis estimates were respectively 78 and 48% under HP, and 75 and 42% under LP. Direct selection under LP was predicted to be 20 to 60% more effective than indirect selection under HP conditions, for hybrid performance under LP. The combining ability estimates provide initial insights into the potential benefit of germplasm from further east in West and Central Africa for developing a male parental pool that is distinct and complimentary to the Malian female pool. On chromosome SBI-05, we found a major A1 CMS fertility restorer locus (Rf5) explaining 19 and 14% of the phenotypic variation in either population. Minor quantitative trait loci (QTL) were detected in these two populations on chromosomes SBI-02, SBI-03, SBI-04 and SBI-10. In the third population, we identified one major A1 CMS fertility restorer locus on chromosome SBI-02, Rf2, explaining 31% of the phenotypic variation in the F2 mapping population. Pentatricopeptide repeat genes in the Rf2 QTL region were sequenced, and we detected in Sobic.002G057050 a missense mutation in the first exon, explaining 81% of the phenotypic variation in an F2:3 validation population and clearly separating B- from R-lines. The Guinea-race hybrids’ substantial yield superiorities over well adapted local Guinea-race varieties suggests that a strategy of breeding hybrids based on Guinea-germplasm can contribute to improving the livelihood of many smallholder farmers in WA. Although the usefulness of direct selection under LP for hybrid performance in the predominantly P-limited target environments was proven, companion evaluations of hybrids under HP would be desirable to identify also new hybrids that can respond to improved fertility conditions for sustainable intensification. The developed KASP marker stands as a promising tool for routine use in WA breeding programs.