Quantitative trait locus-by-environment interaction for milk yield traits on Bos taurus autosome 6

Genotype-by-environment interactions for production traits in dairy cattle have often been observed, while QTL analyses have focused on detecting genes with general effects on production traits. In this study, a QTL search for genes with environmental interaction for the traits milk yield, protein yield, and fat yield were performed on Bos taurus autosome 6 (BTA6), also including information about the previously investigated candidate genes ABCG2 and OPN. The animals in the study were Norwegian Red. Eighteen grandsires and 716 sires were genotyped for 362 markers on BTA6. Every marker bracket was regarded as a putative QTL position. The effects of the candidate genes and the putative QTL were modeled as a regression on an environmental parameter (herd year), which is based on the predicted herd-year effect for the trait. Two QTL were found to have environmentally dependent effects on milk yield. These QTL were located 3.6 cM upstream and 9.1 cM downstream from ABCG2. No environmentally dependent QTL was found to significantly affect protein or fat yield.     

Mapping quantitative trait loci (QTL) in sheep. II. Meta-assembly and identification of novel QTL for milk production traits in sheep

An (Awassi × Merino) × Merino backcross family of 172 ewes was used to map quantitative trait loci (QTL) for different milk production traits on a framework map of 200 loci across all autosomes. From five previously proposed mathematical models describing lactation curves, the Wood model was considered the most appropriate due to its simplicity and its ability to determine ovine lactation curve characteristics. Derived milk traits for milk, fat, protein and lactose yield, as well as percentage composition and somatic cell score were used for single and two-QTL approaches using maximum likelihood estimation and regression analysis. A total of 15 significant (P < 0.01) and additional 25 suggestive (P < 0.05) QTL were detected across both single QTL methods and all traits. In preparation of a meta-analysis, all QTL results were compared with a meta-assembly of QTL for milk production traits in dairy ewes from various public domain sources and can be found on the ReproGen ovine gbrowser http://crcidp.vetsci.usyd.edu.au/cgi-bin/gbrowse/oaries_genome/. Many of the QTL for milk production traits have been reported on chromosomes 1, 3, 6, 16 and 20. Those on chromosomes 3 and 20 are in strong agreement with the results reported here. In addition, novel QTL were found on chromosomes 7, 8, 9, 14, 22 and 24. In a cross-species comparison, we extended the meta-assembly by comparing QTL regions of sheep and cattle, which provided strong evidence for synteny conservation of QTL regions for milk, fat, protein and somatic cell score data between cattle and sheep.     

Meta-analysis of QTL involved in silage quality of maize and comparison with the position of candidate genes

A meta-analysis of quantitative trait loci (QTL) associated with plant digestibility and cell wall composition in maize was carried out using results from 11 different mapping experiments. Statistical methods implemented in “MetaQTL” software were used to build a consensus map, project QTL positions and perform meta-analysis. Fifty-nine QTL for traits associated with digestibility and 150 QTL for traits associated with cell wall composition were included in the analysis. We identified 26 and 42 metaQTL for digestibility and cell wall composition traits, respectively. Fifteen metaQTL with confidence interval (CI) smaller than 10 cM were identified. As expected from trait correlations, 42% of metaQTL for digestibility displayed overlapping CIs with metaQTL for cell wall composition traits. Coincidences were particularly strong on chromosomes 1 and 3. In a second step, 356 genes selected from the MAIZEWALL database as candidates for the cell wall biosynthesis pathway were positioned on our consensus map. Colocalizations between candidate genes and metaQTL positions appeared globally significant based on χ² tests. This study contributed in identifying key chromosomal regions involved in silage quality and potentially associated genes for most of these regions. These genes deserve further investigation, in particular through association mapping.     

Fine mapping quantitative trait loci affecting milk production traits on bovine chromosome 6 in a Chinese Holstein population

To fine map the previously detected quantitative trait loci （QTLs） affecting milk production traits on bovine chromosome 6 （BTA6）, 15 microsatellite markers situated within an interval of 14.3 cM spanning from BMS690 to BM4528 were selected and 918 daughters of 8 sires were genotyped. Two mapping approaches, haplotype sharing based LD mapping and single marker regression mapping, were used to analyze the data. Both approaches revealed a quantitative trait locus （QTL） with significant effects on milk yield, fat yield and protein yield located in the segment flanked by markers BMS483 and MNB209, which spans a genetic distance of 0.6 cM and a physical distance of 1.5 Mb. In addition, the single marker regression mapping also revealed a QTL affecting fat percentage and protein percentage at marker DIK2291. Our fine mapping work will facilitate the cloning of candidate genes underlying the QTLs for milk production traits.     

Mapping and Analysis of Dairy Cattle Quantitative Trait Loci by Maximum Likelihood Methodology Using Milk Protein Genes as Genetic Markers

Maximum likelihood methodology was used to estimate effects of both a marker gene and a linked quantitative trait locus (QTL) on quantitative traits in a segregating population. Two alleles were assumed for the QTL. In addition to the effects of genotypes at both loci on the mean of the quantitative trait, recombination frequency between the loci, frequency of the QTL alleles and the residual standard deviation were also estimated. Thus six parameters were estimated in addition to the marker genotype means. The statistical model was tested on simulated data, and used to estimate direct and linked effects of the milk protein genes, β-lactoglobulin, κcasein, and β-casein, on milk, fat, and protein production and fat and protein percent in the Dutch dairy cattle population. β-Lactoglobulin had significant direct effects on milk yield and fat percent. κ-Casein had significant direct effects on milk yield, protein percent and fat yield. β-Casein had significant direct effects on milk yield, fat and protein percent and fat and protein yield. Linked QTL with significant effects on fat percent were found for κ-casein and β-casein. Since the β-casein and κ-casein genes are closely linked, it is likely that the same QTL was detected for those two markers. Further, a QTL with a significant effect on fat yield was found to be linked to κ-casein and a QTL with a significant effect on protein yield was linked to β-lactoglobulin.     

Quantitative trait loci underlying milk production traits in sheep

Improvement of milk production traits in dairy sheep is required to increase the competitiveness of the industry and to maintain the production of high quality cheese in regions of Mediterranean countries with less favourable conditions. Additional improvement over classical selection could be reached if genes with significant effects on the relevant traits were specifically targeted by selection. However, so far, few studies have been undertaken to detect quantitative trait loci (QTL) in dairy sheep. In this study, we present a complete genome scan performed in a commercial population of Spanish Churra sheep to identify chromosomal regions associated with phenotypic variation observed in milk production traits. Eleven half-sib families, including a total of 1213 ewes, were analysed following a daughter design. Genome-wise multi-marker regression analysis revealed a genome-wise significant QTL for milk protein percentage on chromosome 3. Eight other regions, localized on chromosomes 1, 2, 20, 23 and 25, showed suggestive significant linkage associations with some of the analysed traits. To our knowledge, this study represents the first complete genome scan for milk production traits reported in dairy sheep. The experiment described here shows that analysis of commercial dairy sheep populations has the potential to increase our understanding of the genetic determinants of complex production-related traits.     

Testing for the presence of previously identified QTL for milk production traits in new populations

Five chromosomal regions previously associated with milk production traits were tested in 16 families of Black and White cattle from the UK. The traits were also linearly transformed into genetically and phenotypically independent variables normalized by phenotypic variances ('canonical traits'). Significant associations with the untransformed and canonical traits were found for bovine chromosome 6. There was also evidence that chromosome 9 influenced these traits. The linear transformation clarified the effects of chromosomal regions; regions with effects on all three untransformed traits (milk, fat and protein yields) were generally condensed into an effect on a single canonical trait. Comparison of our results with those reported previously for American Holstein cattle suggested that the QTL may not be the same.     

The identification of QTL that affect the fatty acid composition of milk on sheep chromosome 11

In this work, we analysed 11 genetic markers localized on OAR11 in a commercial population of Spanish Churra sheep to detect QTL that underlie milk fatty acid (FA) composition traits. Following a daughter design, we analysed 799 ewes distributed in 15 half‐sib families. Eight microsatellite markers and three novel SNPs identified in two genes related to fatty acid metabolism, acetyl‐CoA carboxylase α (ACACA) and fatty acid synthase (FASN), were genotyped in the whole population under study. The phenotypic traits considered in the study included 22 measurements related to the FA composition of the milk and three other milk production traits (milk protein percentage, milk fat percentage and milk yield). Across‐family regression analysis revealed four significant QTL at the 5% chromosome‐wise level influencing contents of capric acid (C10:0), lauric acid (C12:0), linoleic conjugated acid (CLA) and polyunsaturated fatty acids (PUFA) respectively. The peaks of the QTL affecting C10:0 and PUFA contents in milk map close to the FASN gene, which has been evaluated as a putative positional candidate for these QTL. The QTL influencing C12:0 content reaches its maximum significance at 58 cM, close to the gene coding for the glucose‐dependent insulinotropic polypeptide. We were not able to find any candidate genes related to fat metabolism at the QTL influencing CLA content, which is located at the proximal end of the chromosome. Further research efforts will be needed to confirm and refine the QTL locations reported here.     

大豆昆虫抗性相关QTLs的元分析

大豆虫害严重危害大豆生产。虽然大豆抗虫相关QTLs研究增多, 但由于作图群体不同、同种昆虫抗性QTL的调查性状不同以及数据分析方法存在差异等原因, 使QTL精确性和有效性被降低。因此, 获得相对真实且有效的QTLs位点对于促进分子标记辅助选择有重要意义。文章通过搜集已报道的81个与大豆昆虫抗性相关的QTL, 提取相对有效且可靠的QTLs标记信息, 利用元分析软件BioMercator2.1将这些QTLs映射到大豆公共遗传连锁图谱Soymap2上, 通过单独与联合的两种元分析途径, 利用QTLs的95%的置信区间来推断“真实QTLs”的位置。文章不仅构建了一张大豆昆虫抗性一致性图谱, 而且通过两种元分析途径分别得到12个和14个QTLs位点, 且其中有6个位点QTL的位置一致。它们被定位在9个连锁群上, 主要成簇分布在E、F、H、M等4个连锁群上, 图距由原来平均15 cM缩减到平均3.67 cM。除了一个与大豆食心虫抗性相关的位点外, 其余QTLs都与多种昆虫抗性相关。研究结果明显缩短了原来已报道的QTL置信区间, 为大豆抗虫相关QTL的精细定位以及抗虫相关基因挖掘提供了依据。     

Genome wide association studies for milk production traits in Chinese Holstein population

Genome-wide association studies (GWAS) based on high throughput SNP genotyping technologies open a broad avenue for exploring genes associated with milk production traits in dairy cattle. Motivated by pinpointing novel quantitative trait nucleotide (QTN) across Bos Taurus genome, the present study is to perform GWAS to identify genes affecting milk production traits using current state-of-the-art SNP genotyping technology, i.e., the Illumina BovineSNP50 BeadChip. In the analyses, the five most commonly evaluated milk production traits are involved, including milk yield (MY), milk fat yield (FY), milk protein yield (PY), milk fat percentage (FP) and milk protein percentage (PP). Estimated breeding values (EBVs) of 2,093 daughters from 14 paternal half-sib families are considered as phenotypes within the framework of a daughter design. Association tests between each trait and the 54K SNPs are achieved via two different analysis approaches, a paternal transmission disequilibrium test (TDT)-based approach (L1-TDT) and a mixed model based regression analysis (MMRA). In total, 105 SNPs were detected to be significantly associated genome-wise with one or multiple milk production traits. Of the 105 SNPs, 38 were commonly detected by both methods, while four and 63 were solely detected by L1-TDT and MMRA, respectively. The majority (86 out of 105) of the significant SNPs is located within the reported QTL regions and some are within or close to the reported candidate genes. In particular, two SNPs, ARS-BFGL-NGS-4939 and BFGL-NGS-118998, are located close to the DGAT1 gene (160bp apart) and within the GHR gene, respectively. Our findings herein not only provide confirmatory evidences for previously findings, but also explore a suite of novel SNPs associated with milk production traits, and thus form a solid basis for eventually unraveling the causal mutations for milk production traits in dairy cattle.     

A search for quantitative trait loci for milk production traits on chromosome 6 in Finnish Ayrshire cattle

Cattle chromosome 6 was scanned with 11 markers, ten microsatellites and the casein haplotype, to identify quantitative trait loci (QTLs) affecting the following milk production traits: milk yield, fat percentage, fat yield, protein percentage and protein yield. Twelve Finnish Ayrshire half-sib families with a total of 480 sons were genotyped and used in a grand-daughter design. Interval mapping was performed with a multiple-marker regression approach with a one-QTL and a two-QTL model, and the significance threshold values were determined empirically using a permutation test. Across-family analysis with the one-QTL model revealed an effect on protein percentage (P < 0.05) and on milk yield (P < 0.05). The analysis with the two-QTL model identified significant effects (P < 0.05) on protein percentage, milk yield, and fat yield. Comparing these two cases, the results suggest the existence of two QTLs on chromosome 6 with an effect on milk production traits. One of the QTLs was located around the casein genes. As the other QTL was similar in location and effect to a QTL found previously in Holstein-Friesians, an identity-by-descent approach could be applied to fine map this region.     

The role of the bovine growth hormone receptor and prolactin receptor genes in milk, fat and protein production in Finnish Ayrshire dairy cattle

We herein report new evidence that the QTL effect on chromosome 20 in Finnish Ayrshire can be explained by variation in two distinct genes, growth hormone receptor (GHR) and prolactin receptor (PRLR). In a previous study in Holstein-Friesian dairy cattle an F279Y polymorphism in the transmembrane domain of GHR was found to be associated with an effect on milk yield and composition. The result of our multimarker regression analysis suggests that in Finnish Ayrshire two QTL segregate on the chromosomal region including GHR and PRLR. By sequencing the coding sequences of GHR and PRLR and the sequence of three GHR promoters from the pooled samples of individuals of known QTL genotype, we identified two substitutions that were associated with milk production traits: the previously reported F-to-Y substitution in the transmembrane domain of GHR and an S-to-N substitution in the signal peptide of PRLR. The results provide strong evidence that the effect of PRLR S18N polymorphism is distinct from the GHR F279Y effect. In particular, the GHR F279Y has the highest influence on protein percentage and fat percentage while PRLR S18N markedly influences protein and fat yield. Furthermore, an interaction between the two loci is suggested.     

Analysis of chromosomal localization of loci controlling milk production traits in cattle

Analysis of the pattern of the chromosomal localization of quantitative trait loci (QTLs) is necessary for comprehensively understanding their functions. The chromosomal localization of QTLs controlling milk production traits has been studied in cattle chromosomes. The distribution of QTLs between chromosomes has proved to be binomial. Their distribution along each chromosome was, in general, uniform, except for the QTLs controlling the somatic cell score (SCS), which tended towards telomeric location. However, there are chromosomes either enriched with or particularly poor in QTLs. The QTL distribution patters are the most similar for the milk yield (M) and milk protein yield (P) and for milk fat yield (F) and milk fat content (%F). The pattern of the SCS QTLs stands out among those of other QTLs. The distance between the QTLs of contrasting traits is the shortest for M and P QTLs, longer for M and milk protein content (%P) QTLs, and still longer for M and %F QTLs, which may be explained by QTL pleiotropy, a common phenomenon in cattle.     

Differential expression of genes in milk of dairy cattle during lactation

The milk fat globule (MFG) is one of the most representative of mammary gland tissues and can be utilized to study gene expression of lactating cows during lactation. In this study, RNA‐seq technology was employed to detect differential expression of genes in MFGs at day 10 and day 70 after calving between two groups of cows with extremely high (H group) and low (L group) 305‐day milk yield, milk fat yield and milk protein yield. In total, 1232, 81, 429 and 178 significantly differentially expressed genes (false discovery rate q < 0.05) were detected between H10 and L10, H70 and L70, H10 and H70, and L10 and L70 respectively. Gene Ontology enrichment and pathway analysis revealed that these differentially expressed genes were enriched in biological processes involved in mammary gland development, protein and lipid metabolism process, signal transduction, cellular process, differentiation and immune function. Among these differentially expressed genes, 178 (H10 vs. L10), 4 (H70 vs. L70), 68 (H10 vs. H70) and 22 (L10 vs. L70) were found to be located within previously reported QTL regions for milk production traits. Based on these results, some promising candidate genes for milk production traits in dairy cattle were suggested.     

Association of the <Emphasis Type="Italic">DGAT1</Emphasis> gene polymorphism in bulls with cow milk performance

The substitution of lysine for alanine (K232A) in the acyl-CoA:diacylglycerol acyltransferase, which is encoded by the DGAT1 gene, was tested for the significance for breeding evaluation of bulls of the holsteinized Black-and-White breed. The breeding value was estimated by the DYDC (daughter yield deviation to contemporaries) method with modification. The frequency of allele 232K in the bulls examined was 0.28, lower than in Holstein bulls (0.4–0.6). The greatest effect of the A232K substitution was observed for the percent fat milk yield (1.4σ) and milk yield (0.76σ), and a lower effect was established for the milk protein yield (0.47σ) and percent protein milk yield (0.44σ). In the case of milk fat yield, the effect was nonsignificant. A method was proposed for converting the data on fat yield in order to obtain significant results in this case as well. The effect of the A232K substitution was estimated at 154 kg for milk yield, 2.8 kg for milk protein yield, 0.079% for percent milk fat, and 0.015% for percent milk protein yield. The results are discussed in the context of multiple pleiotropic effects of the K232A substitution in the DGAT1 gene. It is proposed that the K232A substitution of the DGAT1 gene may be used as a golden standard in comparisons of the effect on milk production traits for the total gene set. This approach will allow a meta-analysis of the gene effects in spite of the different dairy cattle breeds and methods used to analyze their breeding value. In view of more than 30-year experience of using sperm of Holstein bulls, including those breeds in North America, it was noted that the effect of the A232K substitution on milk production traits agreed well with the data reported for the North American commercial population of Holstein cattle.     

Integrating sorghum whole genome sequence information with a compendium of sorghum QTL studies reveals uneven distribution of QTL and of gene-rich regions with significant implications for crop improvement

A comprehensive analysis was conducted using 48 sorghum QTL studies published from 1995 to 2010 to make information from historical sorghum QTL experiments available in a form that could be more readily used by sorghum researchers and plant breeders. In total, 771 QTL relating to 161 unique traits from 44 studies were projected onto a sorghum consensus map. Confidence intervals (CI) of QTL were estimated so that valid comparisons could be made between studies. The method accounted for the number of lines used and the phenotypic variation explained by individual QTL from each study. In addition, estimated centimorgan (cM) locations were calculated for the predicted sorghum gene models identified in Phytozome (JGI GeneModels SBI v1.4) and compared with QTL distribution genome-wide, both on genetic linkage (cM) and physical (base-pair/bp) map scales. QTL and genes were distributed unevenly across the genome. Heterochromatic enrichment for QTL was observed, with approximately 22% of QTL either entirely or partially located in the heterochromatic regions. Heterochromatic gene enrichment was also observed based on their predicted cM locations on the sorghum consensus map, due to suppressed recombination in heterochromatic regions, in contrast to the euchromatic gene enrichment observed on the physical, sequence-based map. The finding of high gene density in recombination-poor regions, coupled with the association with increased QTL density, has implications for the development of more efficient breeding systems in sorghum to better exploit heterosis. The projected QTL information described, combined with the physical locations of sorghum sequence-based markers and predicted gene models, provides sorghum researchers with a useful resource for more detailed analysis of traits and development of efficient marker-assisted breeding strategies.     

Construction of an integrative linkage map and QTL mapping of grain yield-related traits using three related wheat RIL populations

Key message

A novel high-density consensus wheat genetic map was obtained based on three related RIL populations, and the important chromosomal regions affecting yield and related traits were specified.

Abstract

A prerequisite for mapping quantitative trait locus (QTL) is to build a genetic linkage map. In this study, three recombinant inbred line populations (represented by WL, WY, and WJ) sharing one common parental line were used for map construction and subsequently for QTL detection of yield-related traits. PCR-based and diversity arrays technology markers were screened in the three populations. The integrated genetic map contains 1,127 marker loci, which span 2,976.75 cM for the whole genome, 985.93 cM for the A genome, 922.16 cM for the B genome, and 1,068.65 cM for the D genome. Phenotypic values were evaluated in four environments for populations WY and WJ, but three environments for population WL. Individual and combined phenotypic values across environments were used for QTL detection. A total of 165 putative additive QTL were identified, 22 of which showed significant additive-by-environment interaction effects. A total of 65 QTL (51.5 %) were stable across environments, and 23 of these (35.4 %) were common stable QTL that were identified in at least two populations. Notably, QTkw-5B.1, QTkw-6A.2, and QTkw-7B.1 were common major stable QTL in at least two populations, exhibiting 11.28–16.06, 5.64–18.69, and 6.76–21.16 % of the phenotypic variance, respectively. Genetic relationships between kernel dimensions and kernel weight and between yield components and yield were evaluated. Moreover, QTL or regions that commonly interact across genetic backgrounds were discussed by comparing the results of the present study with those of previous similar studies. The present study provides useful information for marker-assisted selection in breeding wheat varieties with high yield.     

Comparative mapping of bovine chromosome 27 with human chromosome 8 near a dairy form QTL in cattle

In the absence of a complete and annotated bovine genome sequence, detailed human-bovine comparative maps are one of the most effective tools for identification of positional candidate genes contributing to quantitative trait loci (QTL) in cattle. In the present study, eight genes from human chromosome 8 were selected for mapping in cattle to improve breakpoint resolution and confirm gene order on the comparative map near the 40 cM region of the BTA27 linkage map where a QTL affecting dairy form had previously been identified. The resulting map identified ADRB3 as a positional candidate gene for the QTL contributing to the dairy form trait based on its estimated position between 40 and 45 cM on the linkage map. It is also a functional candidate gene due to its role in fat metabolism, and polymorphisms in the ADRB3 gene associated with obesity and metabolic disease in humans, as well as, carcass fat in sheep. Further studies are underway to investigate the existence of polymorphisms in the bovine ADRB3 gene and their association with traits related to fat deposition in cattle.     

Confirmation and refinement of a QTL on BTA5 affecting milk production traits in the Fleckvieh dual purpose cattle breed

We analysed a QTL affecting milk yield (MY), milk protein yield (PY) and milk fat yield (FY) in the dual purpose cattle breed Fleckvieh on BTA5. Twenty-six microsatellite markers covering 135 cM were selected to analyse nine half-sib families containing 605 sons in a granddaughter design. We thereby assigned two new markers to the public linkage map using the CRI-MAP program. Phenotypic records were daughter yield deviations (DYD) originating from the routinely performed genetic evaluations of breeding animals. To determine the position of the QTL, three different approaches were applied: interval mapping (IM), linkage analysis by variance component analysis (LAVC), and combined linkage disequilibrium (LD) and linkage (LDL) analysis. All three methods mapped the QTL in the same marker interval ( BM2830-ETH152 ) with the greatest test-statistic value at 118, 119.33 and 119.33 cM respectively. The positive QTL allele simultaneously increases DYD in the first lactation by 272 kg milk, 7.1 kg milk protein and 7.0 kg milk fat. Although the mapping accuracy and the significance of a QTL effect increased from IM over LAVC to LDL, the confidence interval was large (13, 20 and 24 cM for FY, MY and PY respectively) for the positional cloning of the causal gene. The estimated averages of pair wise marker LD with a distance <5 cM were low (0.107) and reflect the large effective population size of the Fleckvieh subpopulation analysed. This low level of LD suggests a need for increase in marker density in following fine mapping steps.     

Detection of QTL for milk production traits in cattle by application of a specifically developed marker map of BTA6

Interval mapping was carried out to identify quantitative trait loci (QTL) for milk production traits in five granddaughter design families of the German Holstein population. Fourteen randomly generated markers spanning the whole of BTA6 and six targeted microsatellite markers from BTA6q21-31 were included in the analysis. In one family a QTL with effects on milk fat yield and milk protein yield was mapped to the interval TGLA37-FBN13 (3 CM proximal to FBN13, lodscore 3.22) in the middle part of the chromosome. Although there are several reports about QTL with effects on milk production traits on BTA6 in the literature, a QTL with effects on milk fat and milk protein yield has not been previously described.