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We propose the use of single nucleotide polymorphisms (SNPs) instead of polymorphic microsatellite markers for individual identification and parentage control in cattle. To this end, we present an initial set of 37 SNP markers together with a gender-specific SNP for identity control and parentage testing in the Holstein, Fleckvieh and Braunvieh breeds. To obtain suitable SNPs, a total of 91.13 kb of random genomic DNA was screened yielding 531 SNPs. These, and 43 previously identified SNPs, were subjected to the following selection criteria: (1) the frequency of the minor allele must be larger than 0.1 in at least two of the three examined breeds, and (2) markers should not be linked closely. Allele frequencies were estimated by analysing sequencing traces of pooled DNA or by genotyping individual DNA samples. The selected SNP loci were physically mapped by radiation hybrid mapping or by fluorescence in situ hybridization, and tested against the neutral mutation hypothesis. The presented marker set theoretically allows probabilities of identity less than 10−13 for individual verification and exclusion powers exceeding 99.99% for parentage testing. [ABSTRACT FROM AUTHOR]

Four and a half LIM domain protein 1 (FHL1) was initially described as an abundant skeletal muscle protein with four LIM domains and a GATA like zinc finger. FHL1 was shown to be expressed in skeletal muscle as well as in a variety of other tissues. Recently, alternatively spliced FHL1 mRNAs were identified coding for C-terminal truncated proteins. The tissue distribution of these variants is more restricted and their functional properties seem to be different. We have isolated and characterized a new variant of FHL1 from porcine skeletal muscle (FHL1C). FHL1C is characterized by a newly identified start codon resulting in a 16 amino acids longer N- terminal region. We have isolated and characterized the porcine FHL1C gene spanning approximately 14 kb and harboring six exons. Using primer extension analysis, the transcription start site of FHL1C was mapped, indicating that FHL1C is regulated by an alternative promoter. The tissue distribution of FHL1C expression was studied by RT-PCR. The porcine FHL1C gene was assigned to the distal part of the long arm of the X chromosome by fluorescence in situ hybridization and screening of a somatic porcine/rodent cell hybrid panel. Copyright © 2000 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

This article reports the localization of the porcine HOXA10 gene to chromosome SSC18q23-q24 by FISH and confirm the position by the use of hybrid panels. PCR amplification to generate a probe for screening of a porcine PAC library was done with primers A. FISH was performed. Statistical analysis revealed a significant correlation of 1.0 between the HOXA10 gene and SSC 18. Within SSC18, chromosome region q13 -q21 indicated the highest probability. The most significantly linked marker is S0120 on SSC18.

Plant genetic resources (PGR) stored at genebanks are humanity's crop diversity savings for the future. Information on PGR contrasted with modern cultivars is key to select PGR parents for pre-breeding. Genotyping-by-sequencing was performed for 7,745 winter wheat PGR samples from the German Federal ex situ genebank at IPK Gatersleben and for 325 modern cultivars. Whole-genome shotgun sequencing was carried out for 446 diverse PGR samples and 322 modern cultivars and lines. In 19 field trials, 7,683 PGR and 232 elite cultivars were characterized for resistance to yellow rust - one of the major threats to wheat worldwide. Yield breeding values of 707 PGR were estimated using hybrid crosses with 36 cultivars - an approach that reduces the lack of agronomic adaptation of PGR and provides better estimates of their contribution to yield breeding. Cross-validations support the interoperability between genomic and phenotypic data. The here presented data are a stepping stone to unlock the functional variation of PGR for European pre-breeding and are the basis for future breeding and research activities., (© 2022. The Author(s).)

The great efforts spent in the maintenance of past diversity in genebanks are rationalized by the potential role of plant genetic resources (PGR) in future crop improvement-a concept whose practical implementation has fallen short of expectations. Here, we implement a genomics-informed prebreeding strategy for wheat improvement that does not discriminate against nonadapted germplasm. We collect and analyze dense genetic profiles for a large winter wheat collection and evaluate grain yield and resistance to yellow rust (YR) in bespoke core sets. Breeders already profit from wild introgressions but PGR still offer useful, yet unused, diversity. Potential donors of resistance sources not yet deployed in breeding were detected, while the prebreeding contribution of PGR to yield was estimated through 'Elite × PGR' F 1 crosses. Genomic prediction within and across genebanks identified the best parents to be used in crosses with elite cultivars whose advanced progenies can outyield current wheat varieties in multiple field trials., (© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Reciprocal recurrent genomic selection is a breeding strategy aimed at improving the hybrid performance of two base populations. It promises to significantly advance hybrid breeding in wheat. Against this backdrop, the main objective of this study was to empirically investigate the potential and limitations of reciprocal recurrent genomic selection. Genome-wide predictive equations were developed using genomic and phenotypic data from a comprehensive population of 1,604 single crosses between 120 female and 15 male wheat lines. Twenty superior female lines were selected for initiation of the reciprocal recurrent genomic selection program. Focusing on the female pool, one cycle was performed with genomic selection steps at the F 2 (60 out of 629 plants) and the F 5 stage (49 out of 382 plants). Selection gain for grain yield was evaluated at six locations. Analyses of the phenotypic data showed pronounced genotype-by-environment interactions with two environments that formed an outgroup compared to the environments used for the genome-wide prediction equations. Removing these two environments for further analysis resulted in a selection gain of 1.0 dt ha -1 compared to the hybrids of the original 20 parental lines. This underscores the potential of reciprocal recurrent genomic selection to promote hybrid wheat breeding, but also highlights the need to develop robust genome-wide predictive equations., Competing Interests: EE and NPf were employed by KWS LOCHOW GmbH. PT, VK, and SK were employed by KWS Saat SE & Co. KGaA. JS, PB, and PV were employed by Limagrain GmbH. EK and NPh was employed by Syngenta Seeds GmbH. NH was employed by Nordsaat Saatzucht GmbH. MG was employed by Nordsaat Saatzucht GmbH and is presently employed by Strube Research GmbH & Co. KG. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Rembe, Reif, Ebmeyer, Thorwarth, Korzun, Schacht, Boeven, Varenne, Kazman, Philipp, Kollers, Pfeiffer, Longin, Hartwig, Gils and Zhao.)

Grain quality traits determine the classification of registered wheat (Triticum aestivum L.) varieties. Although environmental factors and crop management practices exert a considerable influence on wheat quality traits, a significant proportion of the variance is attributed to the genetic factors. To identify the underlying genetic factors of wheat quality parameters viz., grain protein content (GPC), grain starch content (GSC), and grain hardness (GH), we evaluated 372 diverse European wheat varieties in replicated field trials in up to eight environments. We observed that all of the investigated traits hold a wide and significant genetic variation, and a significant negative correlation exists between GPC and GSC plus grain yield. Our association analyses based on 26,694 high-quality single nucleotide polymorphic markers revealed a strong quantitative genetic nature of GPC and GSC with associations on groups 2, 3, and 6 chromosomes. The identification of known Puroindoline-b gene for GH provided a positive analytic proof for our studies. We report that a locus QGpc.ipk-6A controls both GPC and GSC with opposite allelic effects. Based on wheat's reference and pan-genome sequences, the physical characterization of two loci viz., QGpc.ipk-2B and QGpc.ipk-6A facilitated the identification of the candidate genes for GPC. Furthermore, by exploiting additive and epistatic interactions of loci, we evaluated the prospects of predictive breeding for the investigated traits that suggested its efficient use in the breeding programs.

Key Message: Markers, located in Dicer1 and Ara6 genes, which are likely involved in cross-kingdom RNA trafficking, are associated with FHB resistance in GABI wheat population and were validated in biparental population. Association studies are a common approach to detect marker-trait associations for Fusarium head blight (FHB) resistance in wheat (Triticum aestivum), although verification of detected associations is exceptional. In the present study, candidate-gene association mapping (CG) of genes from silencing and secretory pathways, which may be involved in wheat resistance against FHB and cross-kingdom RNA trafficking, was performed. Fourteen markers, located in nine genes, were tested for association with FHB resistance in 356 lines from the GABI (genome analysis of the biological system of plants) wheat population. Three markers located in the genes Dicer1 and Ara6 were shown to be significantly associated with the studied trait. Verification of this finding was performed using the recombinant inbred lines (RILs) population 'Apache × Biscay', segregating for four of our 14 selected markers. We could show association of the Ara6 marker with plant height as well as association with FHB resistance for three markers located in Rab5-like GTPase gene Ara6 and Dicer1. These results confirmed the trait-marker associations detected also in the CG approach. Gene products of the associated genes are involved in response of the plant to pathogens, plant metabolism and may be involved in cross-kingdom RNA trafficking efficiency. The markers detected in the GABI wheat population, which were also validated in the biparental population, can potentially be used in wheat breeding.

Key Message: The genomic selection advantage for Fusarium head blight is promising but failed for Septoria tritici blotch. Selection of new breeding parents based on predictions must be treated with caution. Genomic selection (GS) is an approach that uses whole-genome marker data to estimate breeding values of untested genotypes and holds the potential to improve the genetic gain in breeding programs by shortening the breeding cycle and increasing the selection intensity. However, reported realized gain from genomic selection is limited to few experiments. In this study, a training population of 1120 winter wheat lines derived from 14 bi-parental families was genotyped with genome-wide single nucleotide polymorphism markers and phenotyped for Fusarium head blight (FHB) and Septoria tritici blotch (STB) severity, plant height and heading date. We used weighted ridge regression best linear unbiased prediction to calculate genomic estimated breeding values (GEBVs) of 2500 genotypes. Based on GEBVs, we selected the most resistant individuals as well as a random sample and tested them in a multi-location field trial. We computed moderate coefficients of correlation between observed and predicted trait values for FHB severity, plant height and heading date and achieved a genomic selection advantage of 10.62 percentage points for FHB resistance compared to the randomly chosen subpopulation. Genomic selection failed for the improvement of STB resistance with a genomic selection advantage of only 2.14 percentage points. Our results also indicate that the selection of new breeding parents based on GEBVs must be treated with caution. Taken together, the implementation of GS for FHB resistance, plant height and heading date seems to be promising. For traits with very strong genotype × environment variance, like STB resistance, GS appears to be still challenging.

Genomic selection is an approach that uses whole-genome marker data to predict breeding values of genotypes and holds the potential to improve the genetic gain in breeding programs. In this study, two winter wheat populations (DS1 and DS2) consisting of 438 and 585 lines derived from six and eight bi-parental families, respectively, were genotyped with genome-wide single nucleotide polymorphism markers and phenotyped for Fusarium head blight and Septoria tritici blotch severity, plant height and heading date. We used ridge regression-best linear unbiased prediction to investigate the potential of genomic selection under different selection scenarios: prediction across each winter wheat population, within- and among-family prediction in each population, and prediction from DS1 to DS2 and vice versa. Moreover, we compared a full random model to a model incorporating quantitative trait loci (QTL) as fixed effects. The prediction accuracies obtained by cross-validation within populations were moderate to high for all traits. Accuracies for individual families were in general lower and varied with population size and genetic architecture of the trait. In the among-family prediction scenario, highest accuracies were achieved by predicting from one half-sib family to another, while accuracies were lowest between unrelated families. Our results further demonstrate that the prediction accuracy can be considerably increased by a fixed effect model approach when major QTL are present. Taken together, the implementation of genomic selection for Fusarium head blight and Septoria tritici blotch resistance seems to be promising, but the composition of the training population is of utmost importance.

Background: Barley (Hordeum vulgare) is an important crop cultivated across the world. Drought is a major abiotic factor compromising barley yield worldwide, therefore in modern spring barley cultivars superior seed and malting quality characteristics should be combined with reasonable level of drought tolerance. Previously we have identified a number of barley lines demonstrating the superior yield performance under drought conditions. The aim of this work was to perform a QTL analysis of malting quality traits in a doubled haploid (DH) mapping population of two elite barley lines that differ in their reaction pattern to drought stress., Results: A population of DH lines was developed by crossing two drought-tolerant elite breeding lines, Victoriana and Sofiara, exploiting distinct mechanism of drought tolerance, sustaining assimilation vs remobilization. The mapping population was assayed under field conditions at four distinct locations that differed in precipitation rate. DH lines were genotyped with the Illumina 9 K iSelect assay, and linkage map including 1782 polymorphic markers and covering a total map length of 1140 cM was constructed. The result of quantitative trait loci (QTL) analysis showed that majority of the traits were affected by several main effect QTL and/or QTL x environment (QE) interactions. In total, 57, 41, and 5 QTL were associated with yield-related traits, malting quality traits and seed quality traits, respectively. 11 and 29 of mapped QTL explained more than 10 and 5% of phenotypic variation, respectively. In several chromosomal regions co-localization between QTL for various traits were observed. The largest clusters were detected on chromosomes 3H and 4H., Conclusions: Our QTL mapping results revealed several novel consistent genomic regions controlling malting quality which could be exploited in marker assisted selection. In this context, the complex QTL region on chromosome 3H seems of particular interest, as it harbors several large effect QTL.

Key Message: The dwarfing gene Rht24 on chromosome 6A acts in the wheat population 'Solitär × Bussard', considerably reducing plant height without increasing Fusarium head blight severity and delaying heading stage. The introduction of the Reduced height (Rht)-B1 and Rht-D1 semi-dwarfing genes led to remarkable increases in wheat yields during the Green Revolution. However, their utilization also brings about some unwanted characteristics, including the increased susceptibility to Fusarium head blight. Thus, Rht loci that hold the potential to reduce plant height in wheat without concomitantly increasing Fusarium head blight (FHB) susceptibility are urgently required. The biparental population 'Solitär × Bussard' fixed for the Rht-1 wild-type alleles, but segregating for the recently described gibberellic acid (GA)-sensitive Rht24 gene, was analyzed to identify quantitative trait loci (QTL) for FHB severity, plant height, and heading date and to evaluate the effect of the Rht24 locus on these traits. The most prominent QTL was Rht24 on chromosome 6A explaining 51% of genotypic variation for plant height and exerting an additive effect of - 4.80 cm. For FHB severity three QTL were detected, whereas five and six QTL were found for plant height and heading date, respectively. No FHB resistance QTL was co-localized with QTL for plant height. Unlike the Rht-1 semi-dwarfing alleles, Rht24b did not significantly affect FHB severity. This demonstrates that the choice of semi-dwarfing genes used in plant breeding programs is of utmost consideration where resistance to FHB is an important breeding target.

Grain yield (GY) of bread wheat (Triticum aestivum L.) is quantitatively inherited. Correlated GY-syndrome traits such as plant height (PH), heading date (HD), thousand grain weight (TGW), test weight (TW), grains per ear (GPE), and ear weight (EW) influence GY. Most quantitative genetics studies assessed the multiple-trait (MT) complex of GY-syndrome using single-trait approaches, and little is known about its underlying pleiotropic architecture. We investigated the pleiotropic architecture of wheat GY-syndrome through MT association mapping (MT-GWAS) using 372 varieties phenotyped in up to eight environments and genotyped with 18 832 single nucleotide polymorphisms plus 24 polymorphic functional markers. MT-GWAS revealed a total of 345 significant markers spread genome wide, representing 8, 40, 11, 40, 34, and 35 effective GY-PH, GY-HD, GY-TGW, GY-TW, GY-GPE, and GY-EW associations, respectively. Among them, pleiotropic roles of Rht-B1 and TaGW2-6B loci were corroborated. Only one marker presented simultaneous associations for three traits (i.e. GY-TGW-TW). Close linkage was difficult to differentiate from pleiotropy; thus, the pleiotropic architecture of GY-syndrome was dissected more as a cause of pleiotropy rather than close linkage. Simulations showed that minor allele frequencies, along with sizes and distances between quantitative trait loci for two traits, influenced the ability to distinguish close linkage from pleiotropy., (© The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology.)

Key Message: Compared with independent validation, cross-validation simultaneously sampling genotypes and environments provided similar estimates of accuracy for genomic selection, but inflated estimates for marker-assisted selection. Estimates of prediction accuracy of marker-assisted (MAS) and genomic selection (GS) require validations. The main goal of our study was to compare the prediction accuracies of MAS and GS validated in an independent sample with results obtained from fivefold cross-validation using genomic and phenotypic data for Fusarium head blight resistance in wheat. In addition, the applicability of the reliability criterion, a concept originally developed in the context of classic animal breeding and GS, was explored for MAS. We observed that prediction accuracies of MAS were overestimated by 127% using cross-validation sampling genotype and environments in contrast to independent validation. In contrast, prediction accuracies of GS determined in independent samples are similar to those estimated with cross-validation sampling genotype and environments. This can be explained by small population differentiation between the training and validation sets in our study. For European wheat breeding, which is so far characterized by a slow temporal dynamic in allele frequencies, this assumption seems to be realistic. Thus, GS models used to improve European wheat populations are expected to possess a long-lasting validity. Since quantitative trait loci information can be exploited more precisely if the predicted genotype is more related to the training population, the reliability criterion is also a valuable tool to judge the level of prediction accuracy of individual genotypes in MAS.

Key Message: Genotypes with recombination events in the Triticum ventricosum introgression on chromosome 7D allowed to fine-map resistance gene Pch1, the main source of eyespot resistance in European winter wheat cultivars. Eyespot (also called Strawbreaker) is a common and serious fungal disease of winter wheat caused by the necrotrophic fungi Oculimacula yallundae and Oculimacula acuformis (former name Pseudocercosporella herpotrichoides). A genome-wide association study (GWAS) for eyespot was performed with 732 microsatellite markers (SSR) and 7761 mapped SNP markers derived from the 90 K iSELECT wheat array using a panel of 168 European winter wheat varieties as well as three spring wheat varieties and phenotypic evaluation of eyespot in field tests in three environments. Best linear unbiased estimations (BLUEs) were calculated across all trials and ranged from 1.20 (most resistant) to 5.73 (most susceptible) with an average value of 4.24 and a heritability of H 2  = 0.91. A total of 108 SSR and 235 SNP marker-trait associations (MTAs) were identified by considering associations with a -log 10 (P value) ≥3.0. Significant MTAs for eyespot-score BLUEs were found on chromosomes 1D, 2A, 2D, 3D, 5A, 5D, 6A, 7A and 7D for the SSR markers and chromosomes 1B, 2A, 2B, 2D, 3B and 7D for the SNP markers. For 18 varieties (10.5%), a highly resistant phenotype was detected that was linked to the presence of the resistance gene Pch1 on chromosome 7D. The identification of genotypes with recombination events in the introgressed genomic segment from Triticum ventricosum harboring the Pch1 resistance gene on chromosome 7DL allowed the fine-mapping of this gene using additional SNP markers and a potential candidate gene Traes_7DL_973A33763 coding for a CC-NBS-LRR class protein was identified.

Key Message: This study revealed a complex genetic architecture of male floral traits in wheat, and Rht-D1 was identified as the only major QTL. Genome-wide prediction approaches but also phenotypic recurrent selection appear promising to increase outcrossing ability required for hybrid wheat seed production. Hybrid wheat breeding is a promising approach to increase grain yield and yield stability. However, the identification of lines with favorable male floral characteristics required for hybrid seed production currently poses a severe bottleneck for hybrid wheat breeding. This study therefore aimed to unravel the genetic architecture of floral traits and to assess the potential of genomic approaches to accelerate their improvement. To this end, we employed a panel of 209 diverse winter wheat lines assessed for male floral traits and genotyped with genome-wide markers as well as for Rht-B1 and Rht-D1. We found the highest proportion of explained genotypic variance for the Rht-D1 locus (11-24 %), for which the dwarfing allele Rht-D1b had a negative effect on anther extrusion, visual anther extrusion and pollen mass. The genome-wide scan detected only few QTL with small or medium effects, indicating a complex genetic architecture. Consequently, marker-assisted selection yielded only moderate prediction abilities (0.44-0.63), mainly relying on Rht-D1. Genomic selection based on weighted ridge-regression best linear unbiased prediction achieved higher prediction abilities of up to 0.70 for anther extrusion. In conclusion, recurrent phenotypic selection appears most cost-effective for the initial improvement of floral traits in wheat, while genome-wide prediction approaches may be worthwhile when complete marker profiles are already available in a hybrid wheat breeding program.

Transposable elements (TEs) account for more than 80% of the wheat genome. Although they represent a major obstacle for genomic studies, TEs are also a source of polymorphism and consequently of molecular markers such as insertion site-based polymorphism (ISBP) markers. Insertion site-based polymorphisms have been found to be a great source of genome-specific single-nucleotide polymorphism (SNPs) in the hexaploid wheat ( L.) genome. Here, we report on the development of a high-throughput SNP discovery approach based on sequence capture of ISBP markers. By applying this approach to the reference sequence of chromosome 3B from hexaploid wheat, we designed 39,077 SNPs that are evenly distributed along the chromosome. We demonstrate that these SNPs can be efficiently scored with the KASPar (Kompetitive allele-specific polymerase chain reaction) genotyping technology. Finally, through genetic diversity and genome-wide association studies, we also demonstrate that ISBP-derived SNPs can be used in marker-assisted breeding programs., (Copyright © 2016 Crop Science Society of America.)

Key Message: Genomic prediction of malting quality traits in barley shows the potential of applying genomic selection to improve selection for malting quality and speed up the breeding process., Abstract: Genomic selection has been applied to various plant species, mostly for yield or yield-related traits such as grain dry matter yield or thousand kernel weight, and improvement of resistances against diseases. Quality traits have not been the main scope of analysis for genomic selection, but have rather been addressed by marker-assisted selection. In this study, the potential to apply genomic selection to twelve malting quality traits in two commercial breeding programs of spring and winter barley (Hordeum vulgare L.) was assessed. Phenotypic means were calculated combining multilocational field trial data from 3 or 4 years, depending on the trait investigated. Three to five locations were available in each of these years. Heritabilities for malting traits ranged between 0.50 and 0.98. Predictive abilities (PA), as derived from cross validation, ranged between 0.14 to 0.58 for spring barley and 0.40-0.80 for winter barley. Small training sets were shown to be sufficient to obtain useful PAs, possibly due to the narrow genetic base in this breeding material. Deployment of genomic selection in malting barley breeding clearly has the potential to reduce cost intensive phenotyping for quality traits, increase selection intensity and to shorten breeding cycles.

Grain weight, an essential yield component, is under strong genetic control and at the same time markedly influenced by the environment. Genetic analysis of the thousand grain weight (TGW) by genome-wide association study (GWAS) was performed with a panel of 358 European winter wheat (Triticum aestivum L.) varieties and 14 spring wheat varieties using phenotypic data of field tests in eight environments. Wide phenotypic variations were indicated for the TGW with BLUEs (best linear unbiased estimations) values ranging from 35.9 to 58.2 g with a mean value of 45.4 g and a heritability of H(2) = 0.89. A total of 12 candidate genes for plant height, photoperiodism and grain weight were genotyped on all varieties. Only three candidates, the photoperiodism gene Ppd-D1, dwarfing gene Rht-B1and the TaGW-6A gene were significant explaining up to 14.4, 2.3, and 3.4% of phenotypic variation, respectively. For a comprehensive genome-wide analysis of TGW-QTL genotyping data from 732 microsatellite markers and a set of 7769 mapped SNP-markers genotyped with the 90k iSELECT array were analyzed. In total, 342 significant (-log10 (P-value) ≥ 3.0) marker trait associations (MTAs) were detected for SSR-markers and 1195 MTAs (-log10(P-value) ≥ 3.0) for SNP-markers in all single environments plus the BLUEs. After Bonferroni correction, 28 MTAs remained significant for SSR-markers (-log10 (P-value) ≥ 4.82) and 58 MTAs for SNP-markers (-log10 (P-value) ≥ 5.89). Apart from chromosomes 4B and 6B for SSR-markers and chromosomes 4D and 5D for SNP-markers, MTAs were detected on all chromosomes. The highest number of significant SNP-markers was found on chromosomes 3B and 1B, while for the SSRs most markers were significant on chromosomes 6D and 3D. Overall, TGW was determined by many markers with small effects. Only three SNP-markers had R(2) values above 6%.

Genome-wide mapping approaches in diverse populations are powerful tools to unravel the genetic architecture of complex traits. The main goals of our study were to investigate the potential and limits to unravel the genetic architecture and to identify the factors determining the accuracy of prediction of the genotypic variation of Fusarium head blight (FHB) resistance in wheat (Triticum aestivum L.) based on data collected with a diverse panel of 372 European varieties. The wheat lines were phenotyped in multi-location field trials for FHB resistance and genotyped with 782 simple sequence repeat (SSR) markers, and 9k and 90k single-nucleotide polymorphism (SNP) arrays. We applied genome-wide association mapping in combination with fivefold cross-validations and observed surprisingly high accuracies of prediction for marker-assisted selection based on the detected quantitative trait loci (QTLs). Using a random sample of markers not selected for marker-trait associations revealed only a slight decrease in prediction accuracy compared with marker-based selection exploiting the QTL information. The same picture was confirmed in a simulation study, suggesting that relatedness is a main driver of the accuracy of prediction in marker-assisted selection of FHB resistance. When the accuracy of prediction of three genomic selection models was contrasted for the three marker data sets, no significant differences in accuracies among marker platforms and genomic selection models were observed. Marker density impacted the accuracy of prediction only marginally. Consequently, genomic selection of FHB resistance can be implemented most cost-efficiently based on low- to medium-density SNP arrays.

The genetic architecture of plant height was investigated in a set of 358 recent European winter wheat varieties plus 14 spring wheat varieties based on field data in eight environments. Genotyping of diagnostic markers revealed the Rht-D1b mutant allele in 58% of the investigated varieties, while the Rht-B1b mutant was only present in 7% of the varieties. Rht-D1 was significantly associated with plant height by using a mixed linear model and employing a kinship matrix to correct for population stratification. Further genotyping data included 732 microsatellite markers, resulting in 770 loci, of which 635 markers were placed on the ITMI map plus a set of 7769 mapped SNP markers genotyped with the 90 k iSELECT chip. When Bonferroni correction was applied, a total of 153 significant marker-trait associations (MTAs) were observed for plant height and the SSR markers (-log10 (P-value) ≥ 4.82) and 280 (-log10 (P-value) ≥ 5.89) for the SNPs. Linear regression between the most effective markers and the BLUEs for plant height indicated additive effects for the MTAs of different chromosomal regions. Analysis of syntenic regions in the rice genome revealed closely linked rice genes related to gibberellin acid (GA) metabolism and perception, i.e. GA20 and GA2 oxidases orthologous to wheat chromosomes 1A, 2A, 3A, 3B, 5B, 5D and 7B, ent-kaurenoic acid oxidase orthologous to wheat chromosome 7A, ent-kaurene synthase on wheat chromosome 2B, as well as GA-receptors like DELLA genes orthologous to wheat chromosomes 4B, 4D and 7A and genes of the GID family orthologous to chromosomes 2B and 5B. The data indicated that besides the widely used GA-insensitive dwarfing genes Rht-B1 and Rht-D1 there is a wide spectrum of loci available that could be used for modulating plant height in variety development.

A genome-wide association study (GWAS) for heading date (HD) was performed with a panel of 358 European winter wheat (Triticum aestivum L.) varieties and 14 spring wheat varieties through the phenotypic evaluation of HD in field tests in eight environments. Genotyping data consisted of 770 mapped microsatellite loci and 7934 mapped SNP markers derived from the 90K iSelect wheat chip. Best linear unbiased estimations (BLUEs) were calculated across all trials and ranged from 142.5 to 159.6 days after the 1st of January with an average value of 151.4 days. Considering only associations with a -log10 (P-value) ≥ 3.0, a total of 340 SSR and 2983 SNP marker-trait associations (MTAs) were detected. After Bonferroni correction for multiple testing, a total of 72 SSR and 438 SNP marker-trait associations remained significant. Highly significant MTAs were detected for the photoperiodism gene Ppd-D1, which was genotyped in all varieties. Consistent associations were found on all chromosomes with the highest number of MTAs on chromosome 5B. Linear regression showed a clear dependence of the HD score BLUEs on the number of favorable alleles (decreasing HD) and unfavorable alleles (increasing HD) per variety meaning that genotypes with a higher number of favorable or a low number of unfavorable alleles showed lower HD and therefore flowered earlier. For the vernalization gene Vrn-A2 co-locating MTAs on chromosome 5A, as well as for the photoperiodism genes Ppd-A1 and Ppd-B1 on chromosomes 2A and 2B were detected. After the construction of an integrated map of the SSR and SNP markers and by exploiting the synteny to sequenced species, such as rice and Brachypodium distachyon, we were able to demonstrate that a marker locus on wheat chromosome 5BL with homology to the rice photoperiodism gene Hd6 played a significant role in the determination of the heading date in wheat.

Abiotic stress tolerance in plants is pivotal to increase yield stability, but its genetic basis is still poorly understood. To gain insight into the genetic architecture of frost tolerance, this work evaluated a large mapping population of 1739 wheat (Triticum aestivum L.) lines and hybrids adapted to Central Europe in field trials in Germany and fingerprinted the lines with a 9000 single-nucleotide polymorphism array. Additive effects prevailed over dominance effects. A two-dimensional genome scan revealed the presence of epistatic effects. Genome-wide association mapping in combination with a robust cross-validation strategy identified one frost tolerance locus with a major effect located on chromosome 5B. This locus was not in linkage disequilibrium with the known frost loci Fr-B1 and Fr-B2. The use of the detected diagnostic markers on chromosome 5B, however, does not allow prediction of frost tolerance with high accuracy. Application of genome-wide selection approaches that take into account also loci with small effect sizes considerably improved prediction of the genetic variation of frost tolerance in wheat. The developed prediction model is valuable for improving frost tolerance because this trait displays a wide variation in occurrence across years and is therefore a difficult target for conventional phenotypic selection.

A total of 358 recent European winter wheat varieties plus 14 spring wheat varieties were evaluated for resistance to Fusarium head blight (FHB) caused by Fusarium graminearum and Fusarium culmorum in four separate environments. The FHB scores based on FHB incidence (Type I resistance)×FHB severity (Type II resistance) indicated a wide phenotypic variation of the varieties with BLUE (best linear unbiased estimation) values ranging from 0.07 to 33.67. Genotyping with 732 microsatellite markers resulted in 782 loci of which 620 were placed on the ITMI map. The resulting average marker distance of 6.8 cM allowed genome wide association mapping employing a mixed model. Though no clear population structure was discovered, a kinship matrix was used for stratification. A total of 794 significant (-log10(p)-value≥3.0) associations between SSR-loci and environment-specific FHB scores or BLUE values were detected, which included 323 SSR alleles. For FHB incidence and FHB severity a total of 861 and 877 individual marker-trait associations (MTA) were detected, respectively. Associations for both traits co-located with FHB score in most cases. Consistent associations detected in three or more environments were found on all chromosomes except chromosome 6B, and with the highest number of MTA on chromosome 5B. The dependence of the number of favourable and unfavourable alleles within a variety to the respective FHB scores indicated an additive effect of favourable and unfavourable alleles, i.e. genotypes with more favourable or less unfavourable alleles tended to show greater resistance to FHB. Assessment of a marker specific for the dwarfing gene Rht-D1 resulted in strong effects. The results provide a prerequisite for designing genome wide breeding strategies for FHB resistance.

Background: Single nucleotide polymorphisms (SNPs) are ideal genetic markers due to their high abundance and the highly automated way in which SNPs are detected and SNP assays are performed. The number of SNPs identified in the pig thus far is still limited., Results: A total of 4.8 million whole genome shotgun sequences obtained from the NCBI trace-repository with center name "SDJVP", and project name "Sino-Danish Pig Genome Project" were analysed for the presence of SNPs. Available BAC and BAC-end sequences and their naming and mapping information, all obtained from SangerInstitute FTP site, served as a rough assembly of a reference genome. In 1.2 Gb of pig genome sequence, we identified 98,151 SNPs in which one of the sequences in the alignment represented the polymorphism and 6,374 SNPs in which two sequences represent an identical polymorphism. To benchmark the SNP identification method, 163 SNPs, in which the polymorphism was represented twice in the sequence alignment, were selected and tested on a panel of three purebred boar lines and wild boar. Of these 163 in silico identified SNPs, 134 were shown to be polymorphic in our animal panel., Conclusion: This SNP identification method, which mines for SNPs in publicly available porcine shotgun sequences repositories, provides thousands of high quality SNPs. Benchmarking in an animal panel showed that more than 80% of the predicted SNPs represented true genetic variation.

AMP-activated protein kinase (AMPK) represents the mammalian form of the core component of a kinase cascade that is conserved between fungi, plants, and animals. AMPK plays a major role in protecting mammalian cells from metabolic stress by switching off biosynthetic pathways that require ATP and switching on ATP-regenerating pathways. In this report, we describe the isolation and characterization of the gene for the noncatalytic bovine gamma1 subunit of AMPK. The bovine ampkgamma1 (PRKAG1) gene spans in excess of 14 kb and is located at BTA 5q21-q22. It consists of 12 exons ranging in size from 38 b to 166 b, interspersed with 11 introns that range between 97 b and 6753 b in length. The coding region of the bovine gene shares 93% and 90% nucleotide sequence similarity with its human and rat counterparts, and the bovine AMPKgamma1 protein is 98% and 95% identical to its human and rat homologs, respectively, in amino acid sequence. SNP discovery using a cattle DNA panel revealed a number of polymorphisms that may be useful for the evaluation of ampkgamma1 as a candidate gene for energy metabolism-related production traits.

DGAT1 encodes diacylglycerol O-acyltransferase (EC ), a microsomal enzyme that catalyzes the final step of triglyceride synthesis. It became a functional candidate gene for lactation traits after studies indicated that mice lacking both copies of DGAT1 are completely devoid of milk secretion, most likely because of deficient triglyceride synthesis in the mammary gland. Our mapping studies placed DGAT1 close to the region of a quantitative trait locus (QTL) on bovine chromosome 14 for variation in fat content of milk. Sequencing of DGAT1 from pooled DNA revealed significant frequency shifts at several variable positions between groups of animals with high and low breeding values for milk fat content in different breeds (Holstein-Friesian, Fleckvieh, and Braunvieh). Among the variants was a nonconservative substitution of lysine by alanine (K232A), with the lysine-encoding allele being associated with higher milk fat content. Haplotype analysis indicated the lysine variant to be ancestral. Two animals that were typed heterozygous (Qq) at the QTL based on marker-assisted QTL-genotyping were heterozygous for the K232A substitution, whereas 14 animals that are most likely qq at the QTL were homozygous for the alanine-encoding allele. An independent association study in Fleckvieh animals confirmed the positive effect of the lysine variant on milk fat content. We consider the nonconservative K232A substitution to be directly responsible for the QTL variation, although our genetic studies cannot provide formal proof.

A bovine large-insert DNA library has been constructed in a Bacterial Artificial Chromosome (BAC) vector. The source DNA was derived from lymphocytes of a Jersey male. High-molecular-weight DNA fragments were produced by treatment with EcoRI/EcoRI methylase and cloned into the EcoRI site of pBACe3.6. In total, 157,240 individual BACs have been picked into 384-well plates. Approximately 190 randomly chosen clones have been characterized by Pulsed Field Gel Electrophoresis (PFGE) and have an average insert size of 105 kb, suggesting library coverage representing 5-6 genome equivalents. The frequency of clones without inserts is 4%. The chromosomal location of 51 BACs was studied by FISH; 3 showed more than one signal, indicating a chimerism frequency of roughly 6%. Approximately 50% of the clones in the library contain Simple Repeat Sequences (microsatellites), and 4% of the clones contain centromeric repeats. Insert stability was assessed by restriction digestion of DNA prepared from 20 clones after serial culture for one and three nights. Only one clone showed any evidence of an altered restriction pattern. Clones from 360 x 384-well plates (138,240 colonies) were gridded onto high-density membranes, and PCR superpools were produced from the same set of clones. Both membranes and superpools are available from the RZPD, Berlin (http://www.rzpd.de). PCR 4-D superpools have been prepared from an additional 23,000 clones. The library has been screened for a total of 24 single-copy sequences; positive clones have been obtained in all cases.

A porcine P1-derived artificial chromosome (PAC) library of a male German Landrace pig was constructed in pCYPAC2. In total 90,240 clones were generated and individually transferred into microtiter plates. An average insert size of 119.1 kb was determined by analyzing 150 randomly selected PAC clones by pulsed field electrophoresis, yielding approximately 3.2 genome equivalents. The stability of nine clones was followed through 110 generations showing no reduction of the insert size. The probability of identifying a specific chromosomal region within the library was tested by screening for the presence of seven type I and five type II loci. The analysis showed that most loci (10/12) were present in the library at least twice. To determine the percentage of chimerism, six clones were analyzed by fluorescence in situ hybridization (FISH) on metaphase chromosomes. We assign one type I locus (Triadin) and three type II loci (SW855, S0300, SW1129).