Polymorphisms on SSC15q21-q26 Containing QTL for reproduction in Swine and its association with litter size

Several quantitative trait loci (QTL) for important reproductive traits (ovulation rate) have been identified on the porcine chromosome 15 (SSC15). To assist in the selection of positional candidate swine genes for these QTL on SSC15, twenty-one genes had already been assigned to SSC15 in a previous study in our lab, by using the radiation hybrid panel IMpRH. Further polymorphism studies were carried out on these positional candidate genes with four breeds of pigs (Duroc, Erhualian, Dahuabai and Landrace) harboring significant differences in reproduction traits. A total of nineteen polymorphisms were found in 21 genes. Among these, seven in six genes were used for association studies, whereby NRP2 polymorphism was found to be significantly (p < 0.05) associated with litter-size traits. NRP2 might be a candidate gene for pig-litter size based on its chromosome location (Du et al., 2006), significant association with litter-size traits and relationships with Sema and the VEGF super families.     

Mapping quantitative trait loci affecting female reproductive traits on porcine chromosome 8

An understanding of the genetic control of porcine female reproductive performance would offer the opportunity to utilize natural variation and improve selective breeding programs through marker-assisted selection. The Chinese Meishan is one of the most prolific pig breeds known, farrowing three to five more viable piglets per litter than the European Large White breed. This difference in prolificacy is attributed to the Meishan's superior prenatal survival levels. The present study utilized a three-generation cross in which the founder grandparental animals were purebred Meishan and Large White pigs in a scan for quantitative trait loci (QTL) on porcine chromosome 8 (SSC8) associated with reproductive performance. Reproductive traits, including number of corpora lutea (ovulation rate), teat number, litter size, and prenatal survival, were recorded for as many as 220 F2 females. Putative QTL for the related traits of litter size and prenatal survival were identified at the distal end of the long arm of SSC8. A physiological candidate gene, SPP1, was found to lie within the 95% confidence interval of these QTL. A suggestive QTL for teat number was revealed on the short arm of SSC8. The present study demonstrates, to our knowledge, the first independent confirmation of QTL for fecundity on SSC8, and these QTL regions provide a crucial starting point in the search for the causal genetic variants.     

Quantitative trait locus mapping of fitness-related traits in Drosophila melanogaster

We examined the genetic architecture of four fitness-related traits (reproductive success, ovariole number, body size and early fecundity) in a panel of 98 Oregon-R x 2b3 recombinant inbred lines (RILs). Highly significant genetic variation was observed in this population for female, but not male, reproductive success. The cross-sex genetic correlation for reproductive success was 0.20, which is not significantly different from zero. There was significant genetic variation segregating in this cross for ovariole number, but not for body size or early fecundity. The RILs were genotyped for cytological insertion sites of roo transposable elements, yielding 76 informative markers with an average spacing of 3.2 cM. Quantitative trait loci (QTL) affecting female reproductive success and ovariole number were mapped using a composite interval mapping procedure. QTL for female reproductive success were located at the tip of the X chromosome between markers at cytological locations 1B and 3E; and on the left arm of chromosome 2 in the 30D-38A cytological region. Ovariole number QTL mapped to cytological intervals 62D-69D and 98A-98E, both on the third chromosome. The regions harbouring QTL for female reproductive success and ovariole number were also identified as QTL for longevity in previous studies with these lines.     

Identification of pleiotropic genes and gene sets underlying growth and immunity traits: a case study on Meishan pigs

Both growth and immune capacity are important traits in animal breeding. The animal quantitative trait loci (QTL) database is a valuable resource and can be used for interpreting the genetic mechanisms that underlie growth and immune traits. However, QTL intervals often involve too many candidate genes to find the true causal genes. Therefore, the aim of this study was to provide an effective annotation pipeline that can make full use of the information of Gene Ontology terms annotation, linkage gene blocks and pathways to further identify pleiotropic genes and gene sets in the overlapping intervals of growth-related and immunity-related QTLs. In total, 55 non-redundant QTL overlapping intervals were identified, 1893 growth-related genes and 713 immunity-related genes were further classified into overlapping intervals and 405 pleiotropic genes shared by the two gene sets were determined. In addition, 19 pleiotropic gene linkage blocks and 67 pathways related to immunity and growth traits were discovered. A total of 343 growth-related genes and 144 immunity-related genes involved in pleiotropic pathways were also identified, respectively. We also sequenced and genotyped 284 individuals from Chinese Meishan pigs and European pigs and mapped the single nucleotide polymorphisms (SNPs) to the pleiotropic genes and gene sets that we identified. A total of 971 high-confidence SNPs were mapped to the pleiotropic genes and gene sets that we identified, and among them 743 SNPs were statistically significant in allele frequency between Meishan and European pigs. This study explores the relationship between growth and immunity traits from the view of QTL overlapping intervals and can be generalized to explore the relationships between other traits.     

Do quantitative trait loci (QTL) for a courtship song difference between Drosophila simulans and D. sechellia coincide with candidate genes and intraspecific QTL?

The genetic architecture of traits influencing sexual isolation can give insight into the evolution of reproductive isolation and hence speciation. Here we report a quantitative trait loci (QTL) analysis of the difference in mean interpulse interval (IPI), an important component of the male courtship song, between Drosophila simulans and D. sechellia. Using a backcross analysis, we find six QTL that explain a total of 40.7% of the phenotypic variance. Three candidate genes are located in the intervals bounded by two of the QTL and there are no significant QTL on the X chromosome. The values of mean IPI for hybrid individuals imply the presence of dominant alleles or epistasis. Because unisexual hybrid sterility prevents an F(2) analysis, we cannot distinguish dominant from additive genetic effects at the scale of QTL. A comparison with a study of QTL for intraspecific variation in D. melanogaster shows that, for these strains, the QTL we have identified for interspecific variation cannot be those that contribute to intraspecific variation. We find that the QTL have bidirectional effects, which indicates that the genetic architecture is compatible with divergence due to genetic drift, although other possibilities are discussed.     

穗颈维管性状与产量相关性状的遗传分析

穗颈维管性状是实现"源"合成的同化物输送至籽粒中的唯一通道.本研究利用来源于籼稻93-11(受体)和粳稻日本晴(供体)构建的染色体片段代换系群体,调查穗颈维管性状与穗部产量性状.结果表明,大部分穗颈维管性状与穗部产量性状呈显著相关;7个穗颈维管性状共检测到42个QTL,其中16个位点日本晴等位基因起增效作用;6个穗部产...     

Integration of QTL and bioinformatic tools to identify candidate genes for triglycerides in mice

To identify genetic loci influencing lipid levels, we performed quantitative trait loci (QTL) analysis between inbred mouse strains MRL/MpJ and SM/J, measuring triglyceride levels at 8 weeks of age in F2 mice fed a chow diet. We identified one significant QTL on chromosome (Chr) 15 and three suggestive QTL on Chrs 2, 7, and 17. We also carried out microarray analysis on the livers of parental strains of 282 F2 mice and used these data to find cis-regulated expression QTL. We then narrowed the list of candidate genes under significant QTL using a "toolbox" of bioinformatic resources, including haplotype analysis; parental strain comparison for gene expression differences and nonsynonymous coding single nucleotide polymorphisms (SNP); cis-regulated eQTL in livers of F2 mice; correlation between gene expression and phenotype; and conditioning of expression on the phenotype. We suggest Slc25a7 as a candidate gene for the Chr 7 QTL and, based on expression differences, five genes (Polr3 h, Cyp2d22, Cyp2d26, Tspo, and Ttll12) as candidate genes for Chr 15 QTL. This study shows how bioinformatics can be used effectively to reduce candidate gene lists for QTL related to complex traits.     

QTL analysis of clinical-chemical traits in an F₂ intercross between Landrace and Korean native pigs

Clinical-chemical traits are essential when examining the health status of individuals. The aim of this study was to identify quantitative trait loci (QTL) and the associated positional candidate genes affecting clinical-chemical traits in a reciprocal F(2) intercross between Landrace and Korean native pigs. Following an overnight fast, 25 serum phenotypes related to clinical-chemical traits (e.g., hepatic function parameters, renal function parameters, electrolyte, lipids) were measured in >970 F(2) progeny. All experimental samples were subjected to genotyping analysis using 165 microsatellite markers located across the genome. We identified eleven genome-wide significant QTL in six chromosomal regions (SSC 2, 7, 8, 13, 14, and 15) and 59 suggestive QTL in 17 chromosomal regions (SSC 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 15, 16, 17, and 18). We also observed significant effects of reciprocal crosses on some of the traits, which would seem to result from maternal effect, QTL on sex chromosomes, imprinted genes, or genetic difference in mitochondrial DNA. The role of genomic imprinting in clinical-chemical traits also was investigated. Genome-wide analysis revealed a significant evidence for an imprinted QTL in SSC4 affecting serum amylase levels. Additionally, a series of bivariate linkage analysis provided strong evidence that QTL in SSC 2, 13, 15, and 18 have a pleiotropic effect on clinical-chemical traits. In conclusion, our study detected both novel and previously reported QTL influencing clinical-chemical traits in pigs. The identified QTL together with the positional candidate genes identified here could play an important role in elucidating the genetic structure of clinical-chemical phenotype variation in humans and swine.     

Quantitative trait loci with age-specific effects on fecundity in Drosophila melanogaster

Life-history theory and evolutionary theories of aging assume the existence of alleles with age-specific effects on fitness. While various studies have documented age-related changes in the genetic contribution to variation in fitness components, we know very little about the underlying genetic architecture of such changes. We used a set of recombinant inbred lines to map and characterize the effects of quantitative trait loci (QTL) affecting fecundity of Drosophila melanogaster females at 1 and 4 weeks of age. We identified one QTL on the second chromosome and one or two QTL affecting fecundity on the third chromosome, but these QTL affected fecundity only at 1 week of age. There was more genetic variation for fecundity at 4 weeks of age than at 1 week of age and there was no genetic correlation between early and late-age fecundity. These results suggest that different loci contribute to the variation in fecundity as the organism ages. Our data provide support for the mutation accumulation theory of aging as applied to reproductive senescence. Comparing the results from this study with our previous work on life-span QTL, we also find evidence that antagonistic pleiotropy may contribute to the genetic basis of senescence in these lines as well.     

玉米抗甘蔗花叶病毒基因的比较定位

收集了玉米抗甘蔗花叶病毒基因/QTL定位信息, 借助玉米遗传图谱IBM2 2005 Neighbors进行了整合。在国内外研究中, 累计报道81个抗病毒基因位点, 分布在玉米7条染色体上, 比较定位发现这些位点集中分布于第3和6染色体。采用元分析技术, 确定3个“一致性”抗病毒QTL, 其中1个位于第3染色体, 在遗传图谱IBM2 2005 Neighbors上覆盖的范围为6.44 cM; 2个位于第6染色体, 覆盖范围分别为6.16 cM和27.48 cM。借助比较基因组学策略, 在第3染色体“一致性”QTL区间内筛选出4个抗病位置候选基因。该研究结果为确定和克隆抗病主效基因提供了基础。     

Comparative mapping of a region on chromosome 10 containing QTL for reproduction in swine

Several quantitative trait loci (QTL) for important reproductive traits (age of puberty, ovulation rate, nipple number and plasma FSH) have been identified on the long arm of porcine chromosome 10. Bi-directional chromosome painting has shown that this region is homologous to human chromosome 10p. Because few microsatellite or type I markers have been placed on SSC10, we wanted to increase the density of known ESTs mapped in this region of the porcine genome. Genes were chosen for their position on human chromosome 10, sequence availability from the TIGR pig gene indices, and their potential as a candidate gene. The PCR primers were designed to amplify across introns or 3'-UTR to maximize single nucleotide polymorphism (SNP) discovery. Parents of the mapping population (one sire and seven dams) were amplified and sequenced to find informative markers. The SNPs were genotyped using primer extension and mass spectrometry. These amplification products were also used to probe a BAC library (RPCI-44, Roswell Park Cancer Institute) for positive clones and screened for microsatellites. Six genes from human chromosome 10p (AKR1C2, PRKCQ, ITIH2, ATP5C1, PIP5K2A and GAD2) were mapped in the MARC swine mapping population. Gene order was conserved within these markers from centromere to telomere of porcine chromosome 10q, as compared with human chromosome 10p. Four of these genes (PIP5K2A, ITIH2, GAD2 and AKR1C2), which map under QTL, are potential candidate genes. Identification of porcine homologues near important QTL and development of a comparative map for this chromosome will allow further fine- mapping and positional cloning of candidate genes affecting reproductive traits.     

Mapping of quantitative trait loci for mycoplasma and tetanus antibodies and interferon-gamma in a porcine F2 Duroc × Pietrain resource population

The aim of the present study was to detect quantitative trait loci (QTL) for innate and adaptive immunity in pigs. For this purpose, a Duroc × Pietrain F₂ resource population (DUPI) with 319 offspring was used to map QTL for the immune traits blood antibodies and interferon-gamma using 122 microsatellites covering all autosomes. Antibodies response to Mycoplasma hyopneumoniae and tetanus toxoid vaccine and the interferon-gamma (IFNG) serum concentration were measured at three different time points and were used as phenotypes. The differences of antibodies and interferon concentration between different time points were also used for the linkage mapping. Line-cross and imprinting QTL analysis, including two-QTL, were performed using QTL Express. A total of 30 QTL (12, 6, and 12 for mycoplasma, tetanus antibody, and IFNG, respectively) were identified at the 5% chromosome-wide-level significant, of which 28 were detected by line-cross and 2 by imprinting model. In addition, two QTL were identified on chromosome 5 using the two-QTL approach where both loci were in repulsion phase. Most QTL were detected on pig chromosomes 2, 5, 11, and 18. Antibodies were increased over time and immune traits were found to be affected by sex, litter size, parity, and month of birth. The results demonstrated that antibody and IFNG concentration are influenced by multiple chromosomal areas. The flanking markers of the QTL identified for IFNG on SSC5 did incorporate the position of the porcine IFNG gene. The detected QTL will allow further research in these QTL regions for candidate genes and their utilization in selection to improve the immune response and disease resistance in pig.     

A whole-genome association study for pig reproductive traits

A whole-genome association study was performed for reproductive traits in commercial sows using the PorcineSNP60 BeadChip and Bayesian statistical methods. The traits included total number born (TNB), number born alive (NBA), number of stillborn (SB), number of mummified foetuses at birth (MUM) and gestation length (GL) in each of the first three parities. We report the associations of informative QTL and the genes within the QTL for each reproductive trait in different parities. These results provide evidence of gene effects having temporal impacts on reproductive traits in different parities. Many QTL identified in this study are new for pig reproductive traits. Around 48% of total genes located in the identified QTL regions were predicted to be involved in placental functions. The genomic regions containing genes important for foetal developmental (e.g. MEF2C) and uterine functions (e.g. PLSCR4) were associated with TNB and NBA in the first two parities. Similarly, QTL in other foetal developmental (e.g. HNRNPD and AHR) and placental (e.g. RELL1 and CD96) genes were associated with SB and MUM in different parities. The QTL with genes related to utero-placental blood flow (e.g. VEGFA) and hematopoiesis (e.g. MAFB) were associated with GL differences among sows in this population. Pathway analyses using genes within QTL identified some modest underlying biological pathways, which are interesting candidates (e.g. the nucleotide metabolism pathway for SB) for pig reproductive traits in different parities. Further validation studies on large populations are warranted to improve our understanding of the complex genetic architecture for pig reproductive traits.     

The genetic architecture of ecological specialization: correlated gene effects on host use and habitat choice in pea aphids

Genetic correlations among phenotypic characters result when two traits are influenced by the same genes or sets of genes. By reducing the degree to which traits in two environments can evolve independently (e.g., Lande 1979; Via and Lande 1985), such correlations are likely to play a central role in both the evolution of ecological specialization and in its link to speciation. For example, negative genetic correlations between fitness traits in different environments (i.e., genetic trade-offs) are thought to influence the evolution of specialization, while positive genetic correlations between performance and characters influencing assortative mating can accelerate the evolution of reproductive isolation between ecologically specialized populations. We first discuss how the genetic architecture of a suite of traits may affect the evolutionary role of genetic correlations among them and review how the mechanisms of correlations can be analyzed using quantitative trait locus (QTL) mapping. We then consider the implications of such data for understanding the evolution of specialization and its link to speciation. We illustrate this approach with a QTL analysis of key characters in two races of pea aphids that are highly specialized on different host plants and partially reproductively isolated. Our results suggest that antagonism among QTL effects on performance in the two environments leads to a genetic trade-off in this system. We also found evidence for parallel QTL effects on host-plant acceptance and fecundity on the accepted host, which could produce assortative mating. These results suggest that the genetic architecture of traits associated with host use may have played a central role in the evolution of specialization and reproductive isolation in pea aphids.     

QTL analysis of white blood cell, platelet and red blood cell-related traits in an F2 intercross between Landrace and Korean native pigs

Haematological traits play important roles in disease resistance and defence functions. The objective of this study was to locate quantitative trait loci (QTL) and the associated positional candidate genes influencing haematological traits in an F₂ intercross between Landrace and Korean native pigs. Eight blood‐related traits (six erythrocyte traits, one leucocyte trait and one platelet trait) were measured in 816 F₂ progeny. All experimental animals were genotyped with 173 informative microsatellite markers located throughout the pig genome. We report that nine chromosomes harboured QTL for the baseline blood parameters: genomic regions on SSC 1, 4, 5, 6, 8, 9, 11, 13 and 17. Eight of twenty identified QTL reached genome‐wide significance. In addition, we evaluated the KIT locus, an obvious candidate gene locus affecting variation in blood‐related traits. Using dense single nucleotide polymorphism marker data on SSC 8 and the marker‐assisted association test, the strong association of the KIT locus with blood phenotypes was confirmed. In conclusion, our study identified both previously reported and novel QTL affecting baseline haematological parameters in pigs. Additionally, the positional candidate genes identified here could play an important role in elucidating the genetic architecture of haematological phenotype variation in swine and in humans.     

Genome-Wide Linkage Analysis Identifies Loci for Testicle and Ovary Traits in Chickens

Development of testes or ovaries is critical to chicken breeders. Understanding the genetic mechanisms influencing the development of the testes and ovaries could enhance selection efforts which target reproductive traits. The linkage analysis was conducted within an F2 population derived from Beijing-You chickens and a commercial broiler line. The results have identified one quantitative trait loci (QTL, designated T1) for bilateral testicular weight (TW) and the percentage of TW to carcass weight, and five QTLs (designated O1–O5) for ovary weight (follicle-free, OW) and the percentage of OW to carcass weight. For the testes traits, QTL T1 is located between 6.55 and 8.56 Mb on GGA13. Especially, the gene gamma-amino butyric acid A receptor, alpha 1 (GABRA1) located near the T1 peak. For ovarian traits, QTL O2 was located at 29.31 Mb on GGA7. G protein-coupled receptor 39 (GPR39) present at the O2 peak was expressed at higher levels within the reproductive tract. It is also involved in the regulation of several reproductive functions. Other QTL peaks and the genes’ function in the ovary and testes need to be evaluated. The QTLs and the genes identified in this study could provide valuable information for establishing reproductive traits in chickens, and need further investigation.     

Mapping genes for phosphorus utilization and correlated traits using a 4k SNP linkage map in Japanese quail (Coturnix japonica)

A large F2 cross with 920 Japanese quail was used to map QTL for phosphorus utilization, calcium utilization, feed per gain and body weight gain. In addition, four bone ash traits were included, because it is known that they are genetically correlated with the focal trait of phosphorus utilization. Trait recording was done at the juvenile stage of the birds. The individuals were genotyped genome‐wide for about 4k SNPs and a linkage map constructed, which agreed well with the reference genome. QTL linkage mapping was performed using multimarker regression analysis in a line cross model. Single marker association mapping was done within the mapped QTL regions. The results revealed several genome‐wide significant QTL. For the focal trait phosphorus utilization, a QTL on chromosome CJA3 could be detected by linkage mapping, which was substantiated by the results of the SNP association mapping. Four candidate genes were identified for this QTL, which should be investigated in future functional studies. Some overlap of QTL regions for different traits was detected, which is in agreement with the corresponding genetic correlations. It seems that all traits investigated are polygenic in nature with some significant QTL and probably many other small‐effect QTL that were not detectable in this study.     

Confirmation and fine‐mapping of clinical mastitis and somatic cell score QTL in Nordic Holstein cattle

A genome‐wide association study of 2098 progeny‐tested Nordic Holstein bulls genotyped for 36 387 SNPs on 29 autosomes was conducted to confirm and fine‐map quantitative trait loci (QTL) for mastitis traits identified earlier using linkage analysis with sparse microsatellite markers in the same population. We used linear mixed model analysis where a polygenic genetic effect was fitted as a random effect and single SNPs were successively included as fixed effects in the model. We detected 143 SNP‐by‐trait significant associations (P < 0.0001) on 20 chromosomes affecting mastitis‐related traits. Among them, 21 SNP‐by‐trait combinations exceeded the genome‐wide significant threshold. For 12 chromosomes, both the present association study and the previous linkage study detected QTL, and of these, six were in the same chromosomal locations. Strong associations of SNPs with mastitis traits were observed on bovine autosomes 6, 13, 14 and 20. Possible candidate genes for these QTL were identified. Identification of SNPs in linkage disequilibrium with QTL will enable marker‐based selection for mastitis resistance. The candidate genes identified should be further studied to detect candidate polymorphisms underlying these QTL.     

An Integrative Genomic Analysis of the Superior Fecundity Phenotype in QSi5 Mice

Laboratory inbred mouse models are a valuable resource to identify quantitative trait loci (QTL) for complex reproductive performance traits. Advances in mouse genomics and high density single nucleotide polymorphism mapping has enabled genome-wide association studies to identify genes linked with specific phenotypes. Gene expression profiles of reproductive tissues also provide potentially useful information for identifying genes that play an important role. We have developed a highly fecund inbred strain, QSi5, with accompanying genotyping for comparative analysis of reproductive performance. Here we analyzed the QSi5 phenotype using a comparative analysis with fecundity data derived from 22 inbred strains of mice from the Mouse Phenome Project, and integration with published expression data from mouse ovary development. Using a haplotype association approach, 400 fecundity-associated regions (FDR < 0.05) with 499 underlying genes were identified. The most significant associations were located on Chromosomes 14, 8, and 6, and the genes underlying these regions were extracted. When these genes were analyzed for expression in an ovarian development profile (GSE6916) several distinctive co-expression patterns across each developmental stage were identified. The genetic analysis also refined 21 fecundity associated intervals on Chromosomes 1, 6, 9, 13, and 17 that overlapped with previously reported reproductive performance QTL. The combined use of phenotypic and in silico data with an integrative genomic analysis provides a powerful tool for elucidating the molecular mechanisms underlying fecundity.