Intersubspecific subcongenic mouse strain analysis reveals closely linked QTLs with opposite effects on body weight

A previous genome-wide QTL study revealed many QTLs affecting postnatal body weight and growth in an intersubspecific backcross mouse population between the C57BL/6J (B6) strain and wild Mus musculus castaneus mice captured in the Philippines. Subsequently, several closely linked QTLs for body composition traits were revealed in an F₂ intercross population between B6 and B6.Cg-Pbwg1, a congenic strain on the B6 genetic background carrying the growth QTL Pbwg1 on proximal chromosome 2. However, no QTL affecting body weight has been duplicated in the F₂ population, except for mapping an overdominant QTL that causes heterosis of body weight. In this study, we developed 17 intersubspecific subcongenic strains with overlapping and nonoverlapping castaneus regions from the B6.Cg-Pbwg1 congenic strain in order to search for and genetically dissect QTLs affecting body weight into distinct closely linked loci. Phenotypic comparisons of several developed subcongenic strains with the B6 strain revealed that two closely linked but distinct QTLs that regulate body weight, named Pbwg1.11 and Pbwg1.12, are located on an 8.9-Mb region between D2Mit270 and D2Mit472 and on the next 3.6-Mb region between D2Mit205 and D2Mit182, respectively. Further analyses using F₂ segregating populations obtained from intercrosses between B6 and each of the two selected subcongenic strains confirmed the presence of these two body weight QTLs. Pbwg1.11 had an additive effect on body weight at 6, 10, and 13?weeks of age, and its castaneus allele decreased it. In contrast, the castaneus allele at Pbwg1.12 acted in a dominant fashion and surprisingly increased body weight at 6, 10, and 13?weeks of age despite the body weight of wild castaneus mice being 60% of that of B6 mice. These findings illustrate the complex genetic nature of body weight regulation and support the importance of subcongenic mouse analysis to dissect closely linked loci.     

A growth QTL (<Emphasis Type="Italic">Pbwg1</Emphasis>) region of mouse chromosome 2 contains closely linked loci affecting growth and body composition

Previous QTL studies have identified 24 QTLs for body weight and growth from 3 to 10 weeks after birth in an intersubspecific backcross mouse population between C57BL/6J and wild Mus musculus castaneus that has 60% of the body size of C57BL/6J. The castaneus allele at the most potent QTL (Pbwg1) on proximal chromosome 2 retards growth. In this study we have developed a congenic strain with a 44.1-Mb interval containing the castaneus allele at Pbwg1 by recurrent backcrossing to C57BL/6J. The congenic mouse developed was characterized by significantly higher body weight gain between 1 and 3 weeks of age and lower weight of white fat pads at 10 weeks of age than C57BL/6J. However, no clear difference in body weight at 1–10 weeks of age was observed between congenic and C57BL/6J strains. QTL analysis with 269 F₂ mice between the two strains did not identify any QTLs for body weight at 1, 3, 6, and 10 weeks of age, but it discovered eight closely linked QTLs affecting body weight gain from 1 to 3 weeks of age, lean body weight, weight of white fat pads, and body length within the Pbwg1 region. The castaneus alleles at all fat pad QTLs reduced the phenotypes, whereas at the remaining growth and body composition QTLs, they increased the trait values. These results illustrate that Pbwg1, which initially appeared to be a single locus, was resolved into several loci with opposite effects on the composition traits of overall body weight. This gives a reason for the loss of the Pbwg1 effect found in the original backcross population. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Regulation of Sex Determination in Mice by a Non-coding Genomic Region

To identify novel genomic regions that regulate sex determination, we utilized the powerful C57BL/6J-Y^POS (B6-Y^POS) model of XY sex reversal where mice with autosomes from the B6 strain and a Y chromosome from a wild-derived strain, Mus domesticus poschiavinus (Y^POS), show complete sex reversal. In B6-Y^POS, the presence of a 55-Mb congenic region on chromosome 11 protects from sex reversal in a dose-dependent manner. Using mouse genetic backcross designs and high-density SNP arrays, we narrowed the congenic region to a 1.62-Mb genomic region on chromosome 11 that confers 80% protection from B6-Y^POS sex reversal when one copy is present and complete protection when two copies are present. It was previously believed that the protective congenic region originated from the 129S1/SviMJ (129) strain. However, genomic analysis revealed that this region is not derived from 129 and most likely is derived from the semi-inbred strain POSA. We show that the small 1.62-Mb congenic region that protects against B6-Y^POS sex reversal is located within the Sox9 promoter and promotes the expression of Sox9, thereby driving testis development within the B6-Y^POS background. Through 30 years of backcrossing, this congenic region was maintained, as it promoted male sex determination and fertility despite the female-promoting B6-Y^POS genetic background. Our findings demonstrate that long-range enhancer regions are critical to developmental processes and can be used to identify the complex interplay between genome variants, epigenetics, and developmental gene regulation.     

Searching for Genomic Region of High-Fat Diet-Induced Type 2 Diabetes in Mouse Chromosome 2 by Analysis of Congenic Strains

SMXA-5 mice are a high-fat diet-induced type 2 diabetes animal model established from non-diabetic SM/J and A/J mice. By using F2 intercross mice between SMXA-5 and SM/J mice under feeding with a high-fat diet, we previously mapped a major diabetogenic QTL (T2dm2sa) on chromosome 2. We then produced the congenic strain (SM.A-T2dm2sa (R0), 20.8–163.0 Mb) and demonstrated that the A/J allele of T2dm2sa impaired glucose tolerance and increased body weight and body mass index in the congenic strain compared to SM/J mice. We also showed that the combination of T2dm2sa and other diabetogenic loci was needed to develop the high-fat diet-induced type 2 diabetes. In this study, to narrow the potential genomic region containing the gene(s) responsible for T2dm2sa, we constructed R1 and R2 congenic strains. Both R1 (69.6–163.0 Mb) and R2 (20.8–128.2 Mb) congenic mice exhibited increases in body weight and abdominal fat weight and impaired glucose tolerance compared to SM/J mice. The R1 and R2 congenic analyses strongly suggested that the responsible genes existed in the overlapping genomic interval (69.6–128.2 Mb) between R1 and R2. In addition, studies using the newly established R1A congenic strain showed that the narrowed genomic region (69.6–75.4 Mb) affected not only obesity but also glucose tolerance. To search for candidate genes within the R1A genomic region, we performed exome sequencing analysis between SM/J and A/J mice and extracted 4 genes (Itga6, Zak, Gpr155, and Mtx2) with non-synonymous coding SNPs. These four genes might be candidate genes for type 2 diabetes caused by gene-gene interactions. This study indicated that one of the genes responsible for high-fat diet-induced diabetes exists in the 5.8 Mb genomic interval on mouse chromosome 2.     

A large QTL for fear and anxiety mapped using an F2 cross can be dissected into multiple smaller QTLs

Using chromosome substitution strains (CSS), we previously identified a large quantitative trait locus (QTL) for conditioned fear (CF) on mouse chromosome 10. Here, we used an F₂ cross between CSS‐10 and C57BL/6J (B6) to localize that QTL to distal chromosome 10. That QTL accounted for all the difference between CSS‐10 and B6. We then produced congenic strains to fine‐map that interval. We identified two congenic strains that captured some or all the QTL. The larger congenic strain (Line 1: 122.387121–129.068 Mb; build 37) appeared to account for all the difference between CSS‐10 and B6. The smaller congenic strain (Line 2: 127.277–129.068 Mb) was intermediate between CSS‐10 and B6. We used haplotype mapping followed by quantitative polymerase chain reaction to identify one gene that was differentially expressed in both lines relative to B6 (Rnf41) and one that was differentially expressed between only Line 1 and B6 (Shmt2). These cis‐eQTLs may cause the behavioral QTLs; however, further studies are required to validate these candidate genes. More generally, our observation that a large QTL mapped using CSS and F₂ crosses can be dissected into multiple smaller QTLs shows a weaknesses of two‐stage approaches that seek to use coarse mapping to identify large regions followed by fine‐mapping. Indeed, additional dissection of these congenic strains might result in further subdivision of these QTL regions. Despite these limitations, we have successfully fine‐mapped two QTLs to small regions and identified putative candidate genes, showing that the congenic approach can be effective for fine‐mapping QTLs .     

Genetic loci affecting body weight and fatness in a C57BL/6J × PWK/PhJ mouse intercross

To determine the genetic variation that contributes to body composition in the mouse, we interbred a wild-derived strain (PWK/PhJ; PWK) with a common laboratory strain (C57BL/6J; B6). The parental, F₁, and F₂ mice were phenotyped at 18 weeks old for body weight and composition using dual-energy X-ray absorptiometry (DEXA). A total of 479 (244 male and 235 female) F₂ mice were genotyped for 117 polymorphic markers spanning the autosomes. Twenty-eight suggestive or significant linkages for four traits (body weight, adjusted lean and fat weight, and percent fat) were detected. Of these, three QTLs were novel: one on the proximal portion of Chr 5 for body weight (Bwq8; LOD = 4.7), one on Chr 3 for lean weight (Bwtq13; LOD = 3.6), and one on Chr 11 for percent fat (Adip19; LOD = 5.8). The remaining QTLs overlapped previously identified linkages, e.g., Adip5 on Chr 9. One QTL was sex-specific (present in males only) and seven were sex-biased (more prominent in one sex than the other). Most alleles that increased body weight were contributed by the B6 strain, and most alleles that increased percent fat were contributed by the PWK strain. Eight pairs of interacting loci were identified, none of which exactly overlapped the main-effect QTLs. Many of the QTLs found in the B6 × PWK cross map to the location of previously reported linkages, suggesting that some QTLs are common to many strains (consensus QTLs), but three new QTLs appear to be particular to the PWK strain. The location and type of QTLs detected in this new cross will assist in future efforts to identify the genetic variation that determines the ratio of lean to fat weight as well as body size in mice.     

In silico integration of quantitative trait loci for seed yield and yield-related traits in Brassica napus

Mapping quantitative trait loci (QTLs) is a foundation for molecular marker-assisted selection and map-based gene cloning. During the past decade, numerous QTLs for seed yield (SY) and yield-related traits in Brassica napus L. have been identified. However, integration of these results in order to compare QTLs from different mapping populations has not been undertaken, due to the lack of common molecular markers between studies. Using previously reported Brassica rapa and Brassica oleracea genome sequences, we carried out in silico integration of 1,960 QTLs associated with 13 SY and yield-related traits from 15 B. napus mapping experiments over the last decade. A total of 736 SY and yield-related QTLs were mapped onto 283 loci in the A and C genomes of B. napus. These QTLs were unevenly distributed across the 19 B. napus chromosomes, with the most on chromosome A3 and the least on chromosome C6. Our integrated QTL map identified 142 loci where the conserved QTLs were detected and 25 multifunctional loci, mostly for the traits of flowering time (FT), plant height, 1,000-seed weight, maturity time and SY. These conserved QTLs and multifunctional loci may result from pleiotropism or clustered genes. At the same time, a total of 146 genes underlying the QTLs for FT and other yield-related traits were identified by comparative mapping with the Arabidopsis genome. These results facilitate the retrieval of B. napus SY and yield-related QTLs for research communities, increase the density of targeted QTL-linked markers, validate the existence of QTLs across different populations, and advance the fine mapping of genes.     

Dissecting Quantitative Trait Loci for Boron Efficiency across Multiple Environments in Brassica napus

High yield is the most important goal in crop breeding, and boron (B) is an essential micronutrient for plants. However, B deficiency, leading to yield decreases, is an agricultural problem worldwide. Brassica napus is one of the most sensitive crops to B deficiency, and considerable genotypic variation exists among different cultivars in response to B deficiency. To dissect the genetic basis of tolerance to B deficiency in B. napus, we carried out QTL analysis for seed yield and yield-related traits under low and normal B conditions using the double haploid population (TNDH) by two-year and the BQDH population by three-year field trials. In total, 80 putative QTLs and 42 epistatic interactions for seed yield, plant height, branch number, pod number, seed number, seed weight and B efficiency coefficient (BEC) were identified under low and normal B conditions, singly explaining 4.15–23.16% and 0.53–14.38% of the phenotypic variation. An additive effect of putative QTLs was a more important controlling factor than the additive-additive effect of epistatic interactions. Four QTL-by-environment interactions and 7 interactions between epistatic interactions and the environment contributed to 1.27–4.95% and 1.17–3.68% of the phenotypic variation, respectively. The chromosome region on A2 of SYLB-A2 for seed yield under low B condition and BEC-A2 for BEC in the two populations was equivalent to the region of a reported major QTL, BE1. The B. napus homologous genes of Bra020592 and Bra020595 mapped to the A2 region and were speculated to be candidate genes for B efficiency. These findings reveal the complex genetic basis of B efficiency in B. napus. They provide a basis for the fine mapping and cloning of the B efficiency genes and for breeding B-efficient cultivars by marker-assisted selection (MAS).     

Quantitative trait loci for seed yield and yield-related traits, and their responses to reduced phosphorus supply in Brassica napus

Background and Aims

One of the key targets of breeding programmes in rapeseed (Brassica napus) is to develop high-yield varieties. However, the lack of available phosphorus (P) in soils seriously limits rapeseed production. The aim of this study was to dissect the genetic control of seed yield and yield-related traits in B. napus grown with contrasting P supplies.

Methods

Two-year field trials were conducted at one site with normal and low P treatments using a population of 124 recombinant inbred lines derived from a cross between ‘B104-2’ and ‘Eyou Changjia’. Seed yield, seed weight, seed number, pod number, plant height, branch number and P efficiency coefficient (PEC) were investigated. Quantitative trait locus (QTL) analysis was performed by composite interval mapping.

Key Results

The phenotypic values of most of the tested traits were reduced under the low P conditions. In total, 74 putative QTLs were identified, contributing 7·3–25·4 % of the phenotypic variation. Of these QTLs, 16 (21·6 %) were detected in two seasons and in the mean value of two seasons, and eight QTLs for two traits were conserved across P levels. Low-P-specific QTLs were clustered on chromosomes A1, A6 and A8. By comparative mapping between Arabidopsis and B. napus, 161 orthologues of 146 genes involved in Arabidopsis P homeostasis and/or yield-related trait control were associated with 45 QTLs corresponding to 23 chromosomal regions. Four gene-based markers developed from genes involved in Arabidopsis P homeostasis were mapped to QTL intervals.

Conclusions

Different genetic determinants were involved in controlling seed yield and yield-related traits in B. napus under normal and low P conditions. The QTLs detected under reduced P supply may provide useful information for improving the seed yield of B. napus in soils with low P availability in marker-assisted selection.     

Quantitative Trait Loci for Light Sensitivity,Body Weight,Body Size,and Morphological Eye Parameters in the Bumblebee,Bombus terrestris

Bumblebees such as Bombus terrestris are essential pollinators in natural and managed ecosystems. In addition, this species is intensively used in agriculture for its pollination services, for instance in tomato and pepper greenhouses. Here we performed a quantitative trait loci (QTL) analysis on B. terrestris using 136 microsatellite DNA markers to identify genes linked with 20 traits including light sensitivity, body size and mass, and eye and hind leg measures. By composite interval mapping (IM), we found 83 and 34 suggestive QTLs for 19 of the 20 traits at the linkage group wide significance levels of p = 0.05 and 0.01, respectively. Furthermore, we also found five significant QTLs at the genome wide significant level of p = 0.05. Individual QTLs accounted for 7.5-53.3% of the phenotypic variation. For 15 traits, at least one QTL was confirmed with multiple QTL model mapping. Multivariate principal components analysis confirmed 11 univariate suggestive QTLs but revealed three suggestive QTLs not identified by the individual traits. We also identified several candidate genes linked with light sensitivity, in particular the Phosrestin-1-like gene is a primary candidate for its phototransduction function. In conclusion, we believe that the suggestive and significant QTLs, and markers identified here, can be of use in marker-assisted breeding to improve selection towards light sensitive bumblebees, and thus also the pollination service of bumblebees.     

Identification of candidate genes of QTLs for seed weight in <Emphasis Type="Italic">Brassica napus</Emphasis> through comparative mapping among <Emphasis Type="Italic">Arabidopsis</Emphasis> and <Emphasis Type="Italic">Brassica</Emphasis>species

Background

Map-based cloning of quantitative trait loci (QTLs) in polyploidy crop species remains a challenge due to the complexity of their genome structures. QTLs for seed weight in B. napus have been identified, but information on candidate genes for identified QTLs of this important trait is still rare.

Results

In this study, a whole genome genetic linkage map for B. napus was constructed using simple sequence repeat (SSR) markers that covered a genetic distance of 2,126.4 cM with an average distance of 5.36 cM between markers. A procedure was developed to establish colinearity of SSR loci on B. napus with its two progenitor diploid species B. rapa and B. oleracea through extensive bioinformatics analysis. With the aid of B. rapa and B. oleracea genome sequences, the 421 homologous colinear loci deduced from the SSR loci of B. napus were shown to correspond to 398 homologous loci in Arabidopsis thaliana. Through comparative mapping of Arabidopsis and the three Brassica species, 227 homologous genes for seed size/weight were mapped on the B. napus genetic map, establishing the genetic bases for the important agronomic trait in this amphidiploid species. Furthermore, 12 candidate genes underlying 8 QTLs for seed weight were identified, and a gene-specific marker for BnAP2 was developed through molecular cloning using the seed weight/size gene distribution map in B. napus.

Conclusions

Our study showed that it is feasible to identify candidate genes of QTLs using a SSR-based B. napus genetic map through comparative mapping among Arabidopsis and B. napus and its two progenitor species B. rapa and B. oleracea. Identification of candidate genes for seed weight in amphidiploid B. napus will accelerate the process of isolating the mapped QTLs for this important trait, and this approach may be useful for QTL identification of other traits of agronomic significance.

     

Fine-mapping alleles for body weight in LG/J �� SM/J F2 and F34 advanced intercross lines

The present study measured variation in body weight using a combined analysis in an F₂ intercross and an F₃₄ advanced intercross line (AIL). Both crosses were derived from inbred LG/J and SM/J mice, which were selected for large and small body size prior to inbreeding. Body weight was measured at 62 (±5) days of age. Using an integrated GWAS and forward model selection approach, we identified 11 significant QTLs that affected body weight on ten different chromosomes. With these results we developed a full model that explained over 18% of the phenotypic variance. The median 1.5-LOD support interval was 5.55 Mb, which is a significant improvement over most prior body weight QTLs. We identified nonsynonymous coding SNPs between LG/J and SM/J mice in order to further narrow the list of candidate genes. Three of the genes with nonsynonymous coding SNPs (Rad23b, Stk33, and Anks1b) have been associated with adiposity, waist circumference, and body mass index in human GWAS, thus providing evidence that these genes may underlie our QTLs. Our results demonstrate that a relatively small number of loci contribute significantly to the phenotypic variance in body weight, which is in marked contrast to the situation in humans. This difference is likely to be the result of strong selective pressure and the simplified genetic architecture, both of which are important advantages of our system.     

Dahl (S x R) Congenic Strain Analysis Confirms and Defines a Chromosome 5 Female-Specific Blood Pressure Quantitative Trait Locus to <7 Mbp

The detection of multiple sex-specific blood pressure (BP) quantitative trait loci (QTLs) in independent total genome analyses of F2 (Dahl S x R)-intercross male and female rat cohorts confirms clinical observations of sex-specific disease cause and response to treatment among hypertensive patients, and mandate the identification of sex-specific hypertension genes/mechanisms. We developed and studied two congenic strains, S.R5A and S.R5B introgressing Dahl R-chromosome 5 segments into Dahl S chromosome 5 region spanning putative BP-f1 and BP-f2 QTLs. Radiotelemetric non-stressed 24-hour BP analysis at four weeks post-high salt diet (8% NaCl) challenge, identified only S.R5B congenic rats with lower SBP (−26.5 mmHg, P = 0.002), DBP (−23.7 mmHg, P = 0.004) and MAP (−25.1 mmHg, P = 0.002) compared with Dahl S female controls at four months of age confirming BP-f1 but not BP-f2 QTL on rat chromosome 5. The S.R5B congenic segment did not affect pulse pressure and relative heart weight indicating that the gene underlying BP-f1 does not influence arterial stiffness and cardiac hypertrophy. The results of our congenic analysis narrowed BP-f1 to chromosome 5 coordinates 134.9–141.5 Mbp setting up the basis for further fine mapping of BP-f1 and eventual identification of the specific gene variant accounting for BP-f1 effect on blood pressure.     

Quantitative Trait Locus Mapping and Candidate Gene Analysis for Plant Architecture Traits Using Whole Genome Re-Sequencing in Rice

Plant breeders have focused on improving plant architecture as an effective means to increase crop yield. Here, we identify the main-effect quantitative trait loci (QTLs) for plant shape-related traits in rice (Oryza sativa) and find candidate genes by applying whole genome re-sequencing of two parental cultivars using next-generation sequencing. To identify QTLs influencing plant shape, we analyzed six traits: plant height, tiller number, panicle diameter, panicle length, flag leaf length, and flag leaf width. We performed QTL analysis with 178 F₇ recombinant in-bred lines (RILs) from a cross of japonica rice line ‘SNUSG1’ and indica rice line ‘Milyang23’. Using 131 molecular markers, including 28 insertion/deletion markers, we identified 11 main- and 16 minor-effect QTLs for the six traits with a threshold LOD value > 2.8. Our sequence analysis identified fifty-four candidate genes for the main-effect QTLs. By further comparison of coding sequences and meta-expression profiles between japonica and indica rice varieties, we finally chose 15 strong candidate genes for the 11 main-effect QTLs. Our study shows that the whole-genome sequence data substantially enhanced the efficiency of polymorphic marker development for QTL fine-mapping and the identification of possible candidate genes. This yields useful genetic resources for breeding high-yielding rice cultivars with improved plant architecture.     

Segregation of a QTL cluster for home-cage activity using a new mapping method based on regression analysis of congenic mouse strains

Recent genetic studies have shown that genetic loci with significant effects in whole-genome quantitative trait loci (QTL) analyses were lost or weakened in congenic strains. Characterisation of the genetic basis of this attenuated QTL effect is important to our understanding of the genetic mechanisms of complex traits. We previously found that a consomic strain, B6-Chr6C^MSM, which carries chromosome 6 of a wild-derived strain MSM/Ms on the genetic background of C57BL/6J, exhibited lower home-cage activity than C57BL/6J. In the present study, we conducted a composite interval QTL analysis using the F2 mice derived from a cross between C57BL/6J and B6-Chr6C^MSM. We found one QTL peak that spans 17.6 Mbp of chromosome 6. A subconsomic strain that covers the entire QTL region also showed lower home-cage activity at the same level as the consomic strain. We developed 15 congenic strains, each of which carries a shorter MSM/Ms-derived chromosomal segment from the subconsomic strain. Given that the results of home-cage activity tests on the congenic strains cannot be explained by a simple single-gene model, we applied regression analysis to segregate the multiple genetic loci. The results revealed three loci (loci 1–3) that have the effect of reducing home-cage activity and one locus (locus 4) that increases activity. We also found that the combination of loci 3 and 4 cancels out the effects of the congenic strains, which indicates the existence of a genetic mechanism related to the loss of QTLs.     

Genetic variation in the pleiotropic association between physical activity and body weight in mice

Background

A sedentary lifestyle is often assumed to lead to increases in body weight and potentially obesity and related diseases but in fact little is known about the genetic association between physical activity and body weight. We tested for such an association between body weight and the distance, duration, and speed voluntarily run by 310 mice from the F₂ generation produced from an intercross of two inbred lines that differed dramatically in their physical activity levels.

Methods

We used a conventional interval mapping approach with SNP markers to search for QTLs that affected both body weight and activity traits. We also conducted a genome scan to search for relationship QTLs (relQTLs), or chromosomal regions that affected an activity trait variably depending on the phenotypic value of body weight.

Results

We uncovered seven quantitative trait loci (QTLs) affecting body weight, but only one co-localized with another QTL previously found for activity traits. We discovered 19 relQTLs that provided evidence for a genetic (pleiotropic) association of physical activity and body weight. The three genotypes at each of these loci typically exhibited a combination of negative, zero, and positive regressions of the activity traits on body weight, the net effect of which was to produce overall independence of body weight from physical activity. We also demonstrated that the relQTLs produced these varying associations through differential epistatic interactions with a number of other epistatic QTLs throughout the genome.

Conclusion

It was concluded that individuals with specific combinations of genotypes at the relQTLs and epiQTLs might account for some of the variation typically seen in plots of the association of physical activity with body weight.     

SNPs associated with body weight and backfat thickness in two pig breeds identified by a genome-wide association study

Growth and fat deposition are important economic traits due to the influence on production in pigs. In this study, a dataset of 1200 pigs with 345,570 SNPs genotyped by sequencing (GBS) was used to conduct a GWAS with single-marker regression method to identify SNPs associated with body weight and backfat thickness (BFT) and to search for candidate genes in Landrace and Yorkshire pigs. A total of 27 and 13 significant SNPs were associated with body weight and BFT, respectively. In the region of 149.85–149.89 Mb on SSC6, the SNP (SSC6: 149876737) for body weight and the SNP (SSC6: 149876507) for BFT were in the same locus region (a gap of 230 bp). Two SNPs were located in the DOCK7 gene, which is a protein-coding gene that plays an important role in pigmentation. Two SNPs located on SSC8: 54567459 and SSC11: 33043081 were found to overlap weight and BFT; however, no candidate gene was found in these regions. In addition, based on other significant SNPs, two positional candidate genes, NSRP1 and CADPS, were proposed to influence weight. In conclusion, this is the first study report using GBS data to identify the significant SNPs for weight and BFT. A total of four particularly interesting SNPs and one potential candidate genes (DOCK7) were found for these traits in domestic pigs. This study improves our knowledge to better understand the complex genetic architecture of weight and BFT, but further validation studies of these candidate loci and genes are recommended in pigs     

Genetic mapping of two components of reproductive isolation between two sibling species of moths,Ostrinia nubilalis and O. scapulalis

We report the quantitative trait loci (QTL) mapping of reproductive isolation traits between Ostrinia nubilalis (the European corn borer) and its sibling species O. scapulalis (the Adzuki bean borer), focusing on two traits: mating isolation (mi) and pheromone production (Pher). Four genetic maps were generated from two backcross families, with two maps (one chromosomal map and one linkage map) per backcross. We located 165–323 AFLP markers on these four maps, resulting in the identification of 27–31 linkage groups, depending on the map considered. No-choice mating experiments with the offspring of each backcross led to the detection of at least two QTLs for mi in different linkage groups. QTLs underlying Pher were located in a third linkage group. The Z heterochromosome was identified by a specific marker (Tpi) and did not carry any of these QTLs. Finally, we considered the global divergence between the two sibling species, distortions of segregation throughout the genome, and the location and effect of mi and Pher QTLs in light of the known candidate genes for reproductive isolation within the genus Ostrinia and, more broadly, in phytophagous insects.     

Validation and dissection of quantitative trait loci for leaf traits in interval RM4923-RM402 on the short arm of rice chromosome 6

Validation and dissection of a QTL region for leaf traits in rice which has been reported in a number of independent studies were conducted. Three sets of near isogenic lines (NILs) were originated from a residual heterozygous line derived the indica cross Zhenshan 97B/Milyang 46. They were overlapping and totally covered a 4.2-Mb heterogenous region extending from RM4923 to RM402 on the short arm of rice chromosome 6. Each NIL set consisted of 10 maternal lines and 10 paternal lines. They were measured for the length, width, perimeter and area of the top three leaves and the number of spikelets per panicle, number of grains per panicle and grain weight per panicle. In NIL sets 6-4 and 6-7, differing in intervals RM4923-RM225 and RM19410-RM6119, respectively, significant variations with the enhancing alleles from the female parent ZS97 were shown for the length, perimeter and area except for the area of the third leaf from top in 6-4, but the effects were lower in 6-4 than in 6-7. No significant effects were detected for the three traits in the remaining NIL set. It was shown that flag leaf length (FLL) is the primary target of the QTLs detected. Two QTLs for FLL linked in repulsion phase were resolved, of which qFLL6.2 located in the 1.19-Mb interval RM3414-RM6917 had a major effect with the enhancing allele from Zhenshan 97B, and qFLL6.1 located in the 946.8-kb interval RM19350-RM19410 had a smaller effect with the enhancing allele from Milyang 46. The two QTLs also exerted pleiotropic effects on the yield traits.     

The QTL within the H2 Complex Involved in the Control of Tuberculosis Infection in Mice Is the Classical Class II H2-Ab1 Gene

The level of susceptibility to tuberculosis (TB) infection depends upon allelic variations in numerous interacting genes. In our mouse model system, the whole-genome quantitative trait loci (QTLs) scan revealed three QTLs involved in TB control on chromosomes 3, 9, and in the vicinity of the H2 complex on chromosome 17. For the present study, we have established a panel of new congenic, MHC-recombinant mouse strains bearing differential small segments of chromosome 17 transferred from the TB-susceptible I/St (H2 ^j) strain onto the genetic background of TB-resistant C57BL/6 (B6) mice (H2 ^b). This allowed narrowing the QTL interval to 17Ch: 33, 77–34, 34 Mb, containing 36 protein-encoding genes. Cloning and sequencing of the H2 ^j allelic variants of these genes demonstrated profound polymorphic variations compare to the H2 ^b haplotype. In two recombinant strains, B6.I-249.1.15.100 and B6.I-249.1.15.139, recombination breakpoints occurred in different sites of the H2-Aβ 1 gene (beta-chain of the Class II heterodimer H2-A), providing polymorphic variations in the domain β1 of the Aβ-chain. These variations were sufficient to produce different TB-relevant phenotypes: the more susceptible B6.I-249.1.15.100 strain demonstrated shorter survival time, more rapid body weight loss, higher mycobacterial loads in the lungs and more severe lung histopathology compared to the more resistant B6.I-249.1.15.139 strain. CD4⁺ T cells recognized mycobacterial antigens exclusively in the context of the H2-A Class II molecule, and the level of IFN-γ-producing CD4⁺ T cells in the lungs was significantly higher in the resistant strain. Thus, we directly demonstrated for the first time that the classical H2- Ab1 Class II gene is involved in TB control. Molecular modeling of the H2-A^j product predicts that amino acid (AA) substitutions in the Aβ-chain modify the motif of the peptide–MHC binding groove. Moreover, unique AA substitutions in both α- and β-chains of the H2-A^j molecule might affect its interactions with the T-cell receptor (TCR).