Browsing by Subject "Association analysis"

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Association analysis of genes controlling variation of flowering time in West and Central African sorghum
(2012) Bhosale, Sankalp; Melchinger, Albrecht E.
Sorghum is extremely important for the food security in the arid to semi-arid regions of West and Central Africa (WCA). A serious constraint to the sorghum production in WCA is the scattered beginning but relatively fixed end of the rainy season among years, forcing farmers to adjust their individual sowing dates according to the start of the rains. Owing to the delayed sowing and fixed end of the rainy season, farmers require varieties that flower at the end of the rainy season, regardless of the sowing date. Photoperiod sensitivity of sorghum accessions is an important adaptation trait that allows flowering or synchronized flowering of the accessions at the end of the rainy season. This is also particularly important in avoiding grain mold, insect and bird damages for early maturing varieties, and incomplete grain filling due to soil water shortage occurring at the end of the season in late maturing varieties. Cultivars with photoperiod sensitivity may have the potential to increase yield and yield stability. Unfortunately, in WCA most of the present day cultivars are photoperiod insensitive. Furthermore, unavailability of simple screening methods in selecting photoperiod sensitive cultivars complicates the situation. Breeding techniques such as marker assisted selection (MAS) by employment of molecular markers would greatly enhance the selection efficiency for this major adaptation trait. Candidate-gene (CG) based association studies can assist in investigating the effect of polymorphisms in flowering time genes on phenotypic variation. Allele-specific molecular markers can be developed after a significant marker-phenotype association is identified. These markers can effectively be used in MAS of photoperiod sensitive sorghum cultivars. In this study we carried out a CG based association analysis to investigate the association between variation for photoperiodic sensitivity of flowering time in sorghum and polymorphisms in six partially amplified genes putatively related to variation in flowering time. Five out of six CGs were known to be involved in photoperiod pathway of flowering time [CRYPTOCHROME 1 (CRY1-b1), CRYPTOCHROME 2 (CRY2), LATE ELONGATED HYPOCOTYL (LHY), GIGANTEA (GI), HEADING DATE 6 (HD6)], and the gene SbD8 was involved in the gibberellic acid (GA) pathway of flowering time. In the first part of the study we determined the presence, the expression and the molecular diversity of genes homologous to the important flowering time gene D8 in maize on a set of 26 sorghum and 20 pearl millet accessions. Homologs of D8 were successfully amplified and tested for their expression in sorghum (SbD8) and pearl millet (PgD8). Pearl millet, because of its autogamous nature, showed higher nucleotide diversity than sorghum, which is an allogamous species. In maize, a 6 bp deletion flanking the SH2-like domain of D8 was found to be significantly associated with flowering by Thornsberry et al. (2001). We found in the PgD8 gene a 3 bp insertion or deletion (Indel) flanking the SH2 domain in the region, which was only conserved between D8 and PgD8. Cluster analysis performed for the D8, SbD8, and PgD8 indicated that maize is more closely related to pearl millet than sorghum. These findings suggest that, similar to maize, the indel in PgD8 flanking the SH2 domain might play an important role in determination of flowering. It is advisable to carry out an association study to reveal the potential role of PgD8 in flowering time control in pearl millet. After successfully amplifying and confirming the expression of SbD8 and PgD8, we carried out the association analysis on the selected CGs. A panel of 219 mostly inbred accessions of sorghum from major sorghum growing areas in WCA was complied. In the second part of the study the association analysis panel of accessions was phenotyped for their flowering response in the field in 2007 in Mali. The entire panel was sown twice (June and July), photoperiod response index (PRI) was estimated as the difference between DFL50% of the two sowing dates of the accessions. The PRI of the accessions showed a wide range from close to zero (photoperiod-insensitive) up to values close to 30 or above (highly-photoperiod sensitive). This result confirmed that the range of response based on the choice of the accessions was appropriate for an association analysis. The plant height reduction observed in accessions sown in July compared to the once sown in June was in accordance with previous studies performed in West African sorghum varieties. The sorghum accessions were genotyped using 27 simple sequence repeat markers. Population structure analysis using software STRUCTURE was carried out to control the false positives in the association analysis. The results showed existence of two subgroups in our sorghum accessions. The first subgroup included mainly race guinea (83%) originating from western West African countries such as Mali and Bukina Faso and the second subgroup included accessions mainly from Nigeria and Niger and also accessions originating from other countries and other major races. The race guinea could clearly be distinguished from the other races. Fisher's exact test for the presence of earliness among subgroups showed that there are significantly (p = 0.06) more early maturing accessions in subgroup one than subgroup two. But there was an absence of a clear structuring pattern. The study suggests that the race, the geographical origin, and maturity of the accessions are the most likely forces behind the observed structuring pattern of the accessions. We found a high level of genetic diversity among the sorghum accessions. Race guinea was found to be the most diverse and race kaura was the least diverse. In general, the estimates of the gene diversity were comparable to previous studies. The results showed that clustering of early-intermediate maturing guinea varieties may have increased the linkage disequilibrium (LD) in subgroup one compared to subgroup two. The differences in the extent of LD between our study and those in the previous studies can be due to the differences in the molecular markers used as well as differences in the racial composition of the accessions studied. In the final part of the study the association analysis was carried out using a mixed-model method. This method takes both population structure and kinship information into account. The candidate genes polymorphism data were obtained by amplifying and sequencing of the chosen genes. The association analysis for the polymorphism found within the CGs was carried out using values of PRI for each accession. From the six genes studied, genes CRY1-b1 and GI had several polymorphic sites which were significantly (p < 0.005) associated with PRI variation in the sorghum panel. The most important polymorphism in the gene CRY1-b1 showed an effect on PRI value of up to -4.2 days. This single nucleotide polymorphism (SNP) at position 722 in CRY1-b1 was located in the flavin adenine dinucleotide binding domain (N-terminal domain) of SbCRY1; hence, this domain appears to be important in photomorphogenesis in sorghum. In the case of the GI gene homolog, SNP888 had the largest effect on PRI of about +8 days. Similar to the studies in rice, the GI gene delayed flowering under June sowing (long-day conditons) and shortened the time to flower in sorghum under July sowing (short-day conditons). Therefore, the action of the GI gene homolog in sorghum might be revealed by a detailed investigation of GI by comparison of sorghum accessions grown under short-day and long-day conditions. In the case of gene SbD8, no significant association with PRI could be found; hence, the potential involvement of this gene in flowering time control of sorghum was not confirmed. Negative Tajima?s D values, of CGs indicated that the genes may have been subjected to adaptive selection as variation in flowering time may confer adaptive advantages in sorghum. The results showed that CG-based association analysis using a mixed model approach can be successfully applied to unravel the genetic variation related to phenotypic variation in flowering time. The polymorphisms significantly associated with PRI can be used to develop cleaved amplified polymorphic sequence markers. Functional markers could also be created directly from the significant SNPs. These molecular markers can serve as powerful tools in MAS for sorghum to identify cultivars sensitive to photoperiod.
Investigations on major gene by polygene and gene by environment interaction in German Holstein dairy cattle
(2014) Streit, Melanie; Bennewitz, Jörn
Putative interaction effects between DGAT1 K232A mutation and the polygenic terms (all genes except DGAT1) were investigated in chapter one. This was done for five milk production traits (milk yield, protein yield, fat yield, protein percentage and fat percentage) in the German Holstein dairy cattle population. Therefore, mixed models are used. The test for interaction relied on the comparison of polygenic variance components depending on the sire?s genotypes at DGAT1 K232A. Found substitution effects were highly significant for all traits. Significant interactions between DGAT1 K232A and the polygenic term were found for milk fat and protein percentage. These interactions could be used in breeding schemes. Depending on the DGAT1 K232A genotypes of the sample, in which the sire will be used, three polygenic breeding values of a sire can be calculated. Because the genotypes of the samples are often unknown and usually heterogeneous, this is not a practical approach. Rank correlations between the three polygenic EBVs were always above 0.95, which suggested very little re-ranking. GxE were studied in chapter two. For this, reaction norm random regression sire models were used in the German Holstein dairy cattle population. Around 2300 sires with a minimum of 50 daughters per sire and at minimum seven first-lactation test day observations per daughter were analyzed. As traits, corrected test day records for milk yield, protein yield, fat yield and somatic cell score (SCS) were used. As environmental descriptors, we used herd test day solutions (htds) for milk traits, milk energy yield or SCS. Second-order orthogonal polynomial regressions were applied to the sire effects. Results showed significant slope variances of the reaction norms, which caused a non-constant additive genetic variance across the environmental ranges considered, which pointed to the presence of minor GxE effects. When the environment improved, the additive genetic variance increased, meaning higher (lower) htds for milk traits (SCS). This was also influenced by pure scaling effects, because the non-genetic variance increased in an improved environment and the heritability was less influenced by the environment. For the environmental ranges considered in this study, GxE effects caused very little re-ranking of the sires. To obtain unbiased genetic parameters, it was important to model heterogeneous residual variances. A large genome-wide association analysis was conducted in chapter three to identify SNPs that affect general production (GP) and environmental sensitivity (ES) of milk traits. Around 13 million daughter records were used to calculate sire estimates for GP and ES with help of linear reaction norm models. Daughters were offspring from 2297 sires. The sires were genotyped with a 54k SNP chip. As environmental descriptor, the average milk energy yield performance of the herds at the time where the daughter observations were recorded was used. The sire estimates were used as observations in genome-wide association analyses using 1797 sires. With help of an independent validation set (500 sires of the same population), significant SNPs were confirmed. To separate GxE scaling and other GxE effects, the observations were log-transformed. GxE effects could be found with help of reaction norm models and numerous significant SNPs could be validated for GP and ES, whereas many SNPs affecting GP also affected ES. ES of milk traits is a typical quantitative trait, which is controlled by many genes with small effects and few genes with larger effect. Effects of some SNPs for ES were not removable by log-transformation of observations, indicating that these are not solely scaling effects. Positions of founded clusters were often in well-known candidate regions affecting milk traits. No SNPs, which show effects for GP and ES in opposite directions could be found. Environmental descriptor in GxE analyses is often modelled by average herd milk production levels. Another possibility could be the level of hygiene and udder health. In chapter four, the same models were used as in chapter three. A genome-wide association analysis was done using htds for SCS as an environmental descriptor. With help of this, several SNP clusters affecting intercept and slope could be detected and confirmed. Many SNPs or clusters affecting intercept and slope could be identified, but in total, the number of SNPs affecting intercept was larger. The same SNPs could be detected and validated with and without considering GxE in reaction norm models. Some SNPs affecting only slope were found. For slope, nearly the same SNPs could be found with SCS as an environmental descriptor as presented in chapter three, although both environmental descriptors were only slightly correlated.
Phenotypic and genetic analysis of meat production traits in German Merinoland purebred and crossbred lambs
(2016) Schiller, Katja; Bennewitz, Jörn
The overall aims of the present thesis were to investigate various meat quality (MQ) traits including branched chain fatty acids and their correlation to sensory traits and to perform DNA-based and quantitative genetic analysis for growth, carcass and MQ traits using the data set with about 1600 phenotyped lambs. The lambs were Merinoland (ML) lambs and lambs of five crossbreds of meat type sire breeds and Merinoland ewes. The crosses were CH (Charollais × ML), IF (Ile de France × ML), SK (German black-headed mutton sheep (BHM) × ML), SU (Suffolk × ML) and TX (Texel × ML). In chapter one, growth curves, daily gain and feed conversion of ML sheep and the five ML crosses were investigated via mixed linear models. Linear and Gompertz models were fitted and the quality of fit was assessed. Differences in the model parameters were detected between crosses, genders and birth types. According to the parameters, coefficient of determination and mean square error, the Gompertz provided a better fit compared to the linear model. Additionally feed conversion rate and daily gain were observed, with only the crosses IF and TX showing significant superiority in these traits compared to purebred ML. For practical reasons, however, the common trait daily gain can be recommended to use for breeding purpose, despite if altering the shape of a growth curve is attractive because of e.g. possible lower maintenance costs for a flock. In chapter two, lamb meat and fat of the crosses and ML was investigated for concentration of three branched chain fatty acids (4-Me8:0, 4-ET8:0 and 4-Me9:0) and its correlation to sensory abnormality. Differences between crosses and between sexes were determined, but no significant correlations to sensory traits were found. In chapters three to five, genetic background and genetic parameters were investigated and a chromosome-wide association study imputing SNP panels was undertaken. Furthermore, the possibilities of implementation of this data to improve breeding programs were discussed. Chapter three focuses on genetic parameters of growth, carcass and MQ traits in purebred ML and crossbred lambs. A series of analyses for twelve traits were performed and heritabilities and genetic correlations were estimated using general linear mixed models. Several significant correlations and low to moderate heritabilities were found, indicating that selection on these traits is possible. In chapter four, a targeted association mapping was undertaken with about 330 SNPs using two different statistical models, one with estimation of SNP effects across all crosses and the other with SNP effects per cross. The investigated traits were growth, carcass and MQ traits. In this connection, several weak significant SNPs were revealed. In chapter five, F1 lambs were genotyped on selected chromosomes with a very low SNP panel and imputed via Illumina Ovine 50k SNP BeadChip genotypes from the sires and purebred ML. These were included in a haplotype bibliography before. Furthermore, chromosome-wise association analyses using single marker mixed linear models were performed for MQ, carcass, and growth traits. This was done using the imputed genotypes and the trait phenotypes. Several significant associations were detected, e.g. for the traits shoulder width and cutlet area, and these were discussed with regard to other literature reports as well as their use for practical breeding purpose. The thesis ends with a general discussion.