QTL Mapping of Agronomic Waterlogging Tolerance Using Recombinant Inbred Lines Derived from Tropical Maize (Zea mays L) Germplasm

Waterlogging is an important abiotic stress constraint that causes significant yield losses in maize grown throughout south and south-east Asia due to erratic rainfall patterns. The most economic option to offset the damage caused by waterlogging is to genetically incorporate tolerance in cultivars that are grown widely in the target agro-ecologies. We assessed the genetic variation in a population of recombinant inbred lines (RILs) derived from crossing a waterlogging tolerant line (CAWL-46-3-1) to an elite but sensitive line (CML311-2-1-3) and observed significant range of variation for grain yield (GY) under waterlogging stress along with a number of other secondary traits such as brace roots (BR), chlorophyll content (SPAD), % stem and root lodging (S&RL) among the RILs. Significant positive correlation of GY with BR and SPAD and negative correlation with S&RL indicated the potential use of these secondary traits in selection indices under waterlogged conditions. RILs were genotyped with 331 polymorphic single nucleotide polymorphism (SNP) markers using KASP (Kompetitive Allele Specific PCR) Platform. QTL mapping revealed five QTL on chromosomes 1, 3, 5, 7 and 10, which together explained approximately 30% of phenotypic variance for GY based on evaluation of RIL families under waterlogged conditions, with effects ranging from 520 to 640 kg/ha for individual genomic regions. 13 QTL were identified for various secondary traits associated with waterlogging tolerance, each individually explaining from 3 to 14% of phenotypic variance. Of the 22 candidate genes with known functional domains identified within the physical intervals delimited by the flanking markers of the QTL influencing GY and other secondary traits, six have previously been demonstrated to be associated with anaerobic responses in either maize or other model species. A pair of flanking SNP markers has been identified for each of the QTL and high throughput marker assays were developed to facilitate rapid introgression of waterlogging tolerance in tropical maize breeding programs.     

Mapping of QTL associated with waterlogging tolerance during the seedling stage in maize

BACKGROUND AND AIMS: Soil waterlogging is a major environmental stress that suppresses maize (Zea mays) growth and yield. To identify quantitative trait loci (QTL) associated with waterlogging tolerance at the maize seedling stage, a F2 population consisting of 288 F(2:3) lines was created from a cross between two maize genotypes, 'HZ32' (waterlogging-tolerant) and 'K12' (waterlogging-sensitive). METHODS: The F2 population was genotyped and a base-map of 1710.5 cM length was constructed with an average marker space of 11.5 cM based on 177 SSR (simple sequence repeat) markers. QTL associated with root length, root dry weight, plant height, shoot dry weight, total dry weight and waterlogging tolerance coefficient were identified via composite interval mapping (CIM) under waterlogging and control conditions in 2004 (EXP.1) and 2005 (EXP.2), respectively. KEY RESULTS AND CONCLUSIONS: Twenty-five and thirty-four QTL were detected in EXP.1 and EXP.2, respectively. The effects of each QTL were moderate, ranging from 3.9 to 37.3 %. Several major QTL determining shoot dry weight, root dry weight, total dry weight, plant height and their waterlogging tolerance coefficient each mapped on chromosomes 4 and 9. These QTL were detected consistently in both experiments. Secondary QTL influencing tolerance were also identified and located on chromosomes 1, 2, 3, 6, 7 and 10. These QTL were specific to particular traits or environments. Although the detected regions need to be mapped more precisely, the findings and QTL found in this study may provide useful information for marker-assisted selection (MAS) and further genetic studies on maize waterlogging tolerance.     

A Single Locus Is Responsible for Salinity Tolerance in a Chinese Landrace Barley (Hordeum vulgare L.)

Introduction

Salinity and waterlogging are two major abiotic stresses severely limiting barley production. The lack of a reliable screening method makes it very hard to improve the tolerance through breeding programs.

Methods

This work used 188 DH lines from a cross between a Chinese landrace variety, TX9425 (waterlogging and salinity tolerant), and a Japanese malting barley, Naso Nijo (waterlogging and salinity sensitive), to identify QTLs associated with the tolerance.

Results

Four QTLs were found for waterlogging tolerance. The salinity tolerance was evaluated with both a hydroponic system and in potting mixture. In the trial with potting mixture, only one major QTL was identified to associate with salinity tolerance. This QTL explained nearly 50% of the phenotypic variation, which makes it possible for further fine mapping and cloning of the gene. This QTL was also identified in the hydroponic experiment for different salt-related traits. The position of this QTL was located at a similar position to one of the major QTLs for waterlogging tolerance, indicating the possibility of similar mechanisms controlling both waterlogging and salinity tolerance.

Conclusion

The markers associated with the QTL provided a unique opportunity in breeding programs for selection of salinity and waterlogging tolerance.     

Dynamic QTL Analysis and Candidate Gene Mapping for Waterlogging Tolerance at Maize Seedling Stage

Soil waterlogging is one of the major abiotic stresses adversely affecting maize growth and yield. To identify dynamic expression of genes or quantitative trait loci (QTL), QTL associated with plant height, root length, root dry weight, shoot dry weight and total dry weight were identified via conditional analysis in a mixed linear model and inclusive composite interval mapping method at three respective periods under waterlogging and control conditions. A total of 13, 19 and 23 QTL were detected at stages 3D|0D (the period during 0–3 d of waterlogging), 6D|3D and 9D|6D, respectively. The effects of each QTL were moderate and distributed over nine chromosomes, singly explaining 4.14–18.88% of the phenotypic variation. Six QTL (ph6-1, rl1-2, sdw4-1, sdw7-1, tdw4-1 and tdw7-1) were identified at two consistent stages of seedling development, which could reflect a continuous expression of genes; the remaining QTL were detected at only one stage. Thus, expression of most QTL was influenced by the developmental status. In order to provide additional evidence regarding the role of corresponding genes in waterlogging tolerance, mapping of Expressed Sequence Tags markers and microRNAs were conducted. Seven candidate genes were observed to co-localize with the identified QTL on chromosomes 1, 4, 6, 7 and 9, and may be important candidate genes for waterlogging tolerance. These results are a good starting point for understanding the genetic basis for selectively expressing of QTL in different stress periods and the common genetic control mechanism of the co-localized traits.     

Identification of Major QTL for Waterlogging Tolerance Using Genome-Wide Association and Linkage Mapping of Maize Seedlings

To investigate the genetic basis of maize seedling response to waterlogging, we performed a genome-wide association study in 144 maize inbred lines, measuring length, fresh and dry weight of roots and shoots under normal and waterlogged conditions using 45,868 SNPs. This panel was divided into three subgroups based on the population structure results and the LD decay distance was 180 kb. A biparental advanced backcross (AB) population was also used to detect quantitative trait loci (QTL). In a comparison of 16 different models, principal components analysis (PCA/top PC3)?+?K was found to be best for reduction of false-positive associations for further analysis. A whole-genome scan detected four strong peak signals (P <?2.18?×?10^?5) significantly associated with the waterlogging response on chromosomes 5, 6 and 9. SNP4784, SNP200, SNP298, and SNP6314 showed significant association with corresponding traits under waterlogging and explained 14.99–19.36 %, 15.75–17.64 %, 16.08 % and 15.44 % of the phenotypic variation, respectively. The identified SNPs were located in GRMZM2G012046, GRMZM2G009808, GRMZM2G137108 and GRMZM2G369629 (AGPV1). SNP4784 (GRMZM2G012046) was colocalized with the major QTL that was identified with the same traits in the AB population. Forty-seven SNPs significantly associated (P?<?2.18?×?10^?4) with six traits in association mapping were identified and, among these, 33 SNPs were already reported in literature as waterlogging-related traits. These results will help elucidate the genetic basis of differential responses and tolerance to waterlogging stress among maize inbred lines, and provide novel loci for improvement of waterlogging tolerance of maize inbred lines using marker-assisted selection.     

Mapping of yield-related QTLs in pepper in an interspecific cross of <Emphasis Type="Italic">Capsicum annuum</Emphasis> and <Emphasis Type="Italic">C. frutescens</Emphasis>

An advanced backcross QTL study was performed in pepper using a cross between the cultivated species Capsicum annuum cv. Maor and the wild C. frutescens BG 2816 accession. A genetic map from this cross was constructed, based on 248 BC(2) plants and 92 restriction fragment length polymorphism (RFLP) markers distributed throughout the genome. Ten yield-related traits were analyzed in the BC(2) and BC(2)S(1) generations, and a total of 58 quantitative trait loci (QTLs) were detected; the number of QTLs per trait ranged from two to ten. Most of the QTLs were found in 11 clusters, in which similar QTL positions were identified for multiple traits. Unlike the high percentage of favorable QTL alleles discovered in wild species of tomato and rice, only a few such QTL alleles were detected in BG 2816. For six QTLs (10%), alleles with effects opposite to those expected from the phenotype were detected in the wild species. The use of common RFLP markers in the pepper and tomato maps enabled possible orthologous QTLs in the two species to be determined. The degree of putative QTL orthology for the two main fruit morphology traits-weight and shape-varied considerably. While all eight QTLs identified for fruit weight in this study could be orthologous to tomato fruit weight QTLs, only one out of six fruit shape QTLs found in this study could be orthologous to tomato fruit shape QTLs.     

Genome‐wide quantitative trait loci reveal the genetic basis of cotton fibre quality and yield‐related traits in a Gossypium hirsutum recombinant inbred line population

Cotton is widely cultivated globally because it provides natural fibre for the textile industry and human use. To identify quantitative trait loci (QTLs)/genes associated with fibre quality and yield, a recombinant inbred line (RIL) population was developed in upland cotton. A consensus map covering the whole genome was constructed with three types of markers (8295 markers, 5197.17 centimorgans (cM)). Six fibre yield and quality traits were evaluated in 17 environments, and 983 QTLs were identified, 198 of which were stable and mainly distributed on chromosomes 4, 6, 7, 13, 21 and 25. Thirty‐seven QTL clusters were identified, in which 92.8% of paired traits with significant medium or high positive correlations had the same QTL additive effect directions, and all of the paired traits with significant medium or high negative correlations had opposite additive effect directions. In total, 1297 genes were discovered in the QTL clusters, 414 of which were expressed in two RNA‐Seq data sets. Many genes were discovered, 23 of which were promising candidates. Six important QTL clusters that included both fibre quality and yield traits were identified with opposite additive effect directions, and those on chromosome 13 (qClu‐chr13‐2) could increase fibre quality but reduce yield; this result was validated in a natural population using three markers. These data could provide information about the genetic basis of cotton fibre quality and yield and help cotton breeders to improve fibre quality and yield simultaneously.     

Identification of molecular markers for aluminium tolerance in diploid oat through comparative mapping and QTL analysis

The degree of aluminium tolerance varies widely across cereal species, with oats (Avena spp.) being among the most tolerant. The objective of this study was to identify molecular markers linked to aluminium tolerance in the diploid oat A. strigosa. Restriction fragment length polymorphism markers were tested in regions where comparative mapping indicated the potential for orthologous quantitative trait loci (QTL) for aluminium tolerance in other grass species. Amplified fragment length polymorphism (AFLP) and sequence-characterized amplified region (SCAR) markers were used to provide additional coverage of the genome. Four QTL were identified. The largest QTL explained 39% of the variation and is possibly orthologous to the major gene found in the Triticeae as well as Alm1 in maize and a minor gene in rice. A second QTL may be orthologous to the Alm2 gene in maize. Two other QTL were associated with anonymous markers. Together, these QTL accounted for 55% of the variation. A SCAR marker linked to the major QTL identified in this study could be used to introgress the aluminium tolerance trait from A. strigosa into cultivated oat germplasm. Electronic Supplementary Material Supplementary material is available for this article at and is accessible for authorized users. S. Kibite: In Memoriam     

Identifying a Major QTL Associated with Salinity Tolerance in Nile Tilapia Using QTL-Seq

Selection of new lines with high salinity tolerance allows for economically feasible production of tilapias in brackish water areas. Mapping QTLs and identifying the markers linked to salinity-tolerant traits are the first steps in the improvement of the tolerance in tilapia through marker-assisted selection techniques. By using QTL-seq strategy and linkage-based analysis, two significant QTL intervals (chrLG4 and chrLG18) on salinity-tolerant traits were firstly identified in the Nile tilapia. Fine mapping with microsatellite and SNP markers suggested a major QTL region that located at 23.0 Mb of chrLG18 and explained 79% of phenotypic variation with a LOD value of 95. Expression analysis indicated that at least 10 genes (e.g., LACTB2, KINH, NCOA2, DIP2C, LARP4B, PEX5R, and KCNJ9) near or within the QTL interval were significantly differentially expressed in intestines, brains, or gills under 10, 15, or 20 ppt challenges. Our findings suggest that QTL-seq can be effectively utilized in QTL mapping of salinity-tolerant traits in fish. The identified major QTL is a promising locus to improve our knowledge on the genetic mechanism of salinity tolerance in tilapia.     

Comparison of quantitative trait loci for adaptive traits between oak and chestnut based on an expressed sequence tag consensus map

A comparative genetic and QTL mapping was performed between Quercus robur L. and Castanea sativa Mill., two major forest tree species belonging to the Fagaceae family. Oak EST-derived markers (STSs) were used to align the 12 linkage groups of the two species. Fifty-one and 45 STSs were mapped in oak and chestnut, respectively. These STSs, added to SSR markers previously mapped in both species, provided a total number of 55 orthologous molecular markers for comparative mapping within the Fagaceae family. Homeologous genomic regions identified between oak and chestnut allowed us to compare QTL positions for three important adaptive traits. Colocation of the QTL controlling the timing of bud burst was significant between the two species. However, conservation of QTL for height growth was not supported by statistical tests. No QTL for carbon isotope discrimination was conserved between the two species. Putative candidate genes for bud burst can be identified on the basis of colocations between EST-derived markers and QTL.     

Robust tests for matched case-control genetic association studies

Background

Infectious disease of livestock continues to be a cause of substantial economic loss and has adverse welfare consequences in both the developing and developed world. New solutions to control disease are needed and research focused on the genetic loci determining variation in immune-related traits has the potential to deliver solutions. However, identifying selectable markers and the causal genes involved in disease resistance and vaccine response is not straightforward. The aims of this study were to locate regions of the bovine genome that control the immune response post immunisation. 195 F2 and backcross Holstein Charolais cattle were immunised with a 40-mer peptide derived from foot-and-mouth disease virus (FMDV). T cell and antibody (IgG1 and IgG2) responses were measured at several time points post immunisation. All experimental animals (F0, F1 and F2, n = 982) were genotyped with 165 microsatellite markers for the genome scan.

Results

Considerable variability in the immune responses across time was observed and sire, dam and age had significant effects on responses at specific time points. There were significant correlations within traits across time, and between IgG1 and IgG2 traits, also some weak correlations were detected between T cell and IgG2 responses. The whole genome scan detected 77 quantitative trait loci (QTL), on 22 chromosomes, including clusters of QTL on BTA 4, 5, 6, 20, 23 and 25. Two QTL reached 5% genome wide significance (on BTA 6 and 24) and one on BTA 20 reached 1% genome wide significance.

Conclusions

A proportion of the variance in the T cell and antibody response post immunisation with an FDMV peptide has a genetic component. Even though the antigen was relatively simple, the humoral and cell mediated responses were clearly under complex genetic control, with the majority of QTL located outside the MHC locus. The results suggest that there may be specific genes or loci that impact on variation in both the primary and secondary immune responses, whereas other loci may be specifically important for early or later phases of the immune response. Future fine mapping of the QTL clusters identified has the potential to reveal the causal variations underlying the variation in immune response observed.     

QTL analysis of frost damage in pea suggests different mechanisms involved in frost tolerance

Key message

Avoidance mechanisms and intrinsic resistance are complementary strategies to improve winter frost tolerance and yield potential in field pea.

Abstract

The development of the winter pea crop represents a major challenge to expand plant protein production in temperate areas. Breeding winter cultivars requires the combination of freezing tolerance as well as high seed productivity and quality. In this context, we investigated the genetic determinism of winter frost tolerance and assessed its genetic relationship with yield and developmental traits. Using a newly identified source of frost resistance, we developed a population of recombinant inbred lines and evaluated it in six environments in Dijon and Clermont-Ferrand between 2005 and 2010. We developed a genetic map comprising 679 markers distributed over seven linkage groups and covering 947.1 cM. One hundred sixty-one quantitative trait loci (QTL) explaining 9–71 % of the phenotypic variation were detected across the six environments for all traits measured. Two clusters of QTL mapped on the linkage groups III and one cluster on LGVI reveal the genetic links between phenology, morphology, yield-related traits and frost tolerance in winter pea. QTL clusters on LGIII highlighted major developmental gene loci (Hr and Le) and the QTL cluster on LGVI explained up to 71 % of the winter frost damage variation. This suggests that a specific architecture and flowering ideotype defines frost tolerance in winter pea. However, two consistent frost tolerance QTL on LGV were independent of phenology and morphology traits, showing that different protective mechanisms are involved in frost tolerance. Finally, these results suggest that frost tolerance can be bred independently to seed productivity and quality.     

Uncovering QTL for resistance and survival time to Philasterides dicentrarchi in turbot (Scophthalmus maximus)

Disease resistance‐related traits have received increasing importance in aquaculture breeding programs worldwide. Currently, genomic information offers new possibilities in breeding to address the improvement of this kind of traits. The turbot is one of the most promising European aquaculture species, and Philasterides dicentrarchi is a scuticociliate parasite causing fatal disease in farmed turbot. An appealing approach to fight against disease is to achieve a more robust broodstock, which could prevent or diminish the devastating effects of scuticociliatosis on farmed individuals. In the present study, a genome scan for quantitative trait loci (QTL) affecting resistance and survival time to P. dicentrarchi in four turbot families was carried out. The objectives were to identify QTL using different statistical approaches [linear regression (LR) and maximum likelihood (ML)] and to locate significantly associated markers for their application in genetic breeding strategies. Several genomic regions controlling resistance and survival time to P. dicentrarchi were detected. When analyzing each family separately, significant QTL for resistance were identified by the LR method in two linkage groups (LG1 and LG9) and for survival time in LG1, while the ML methodology identified QTL for resistance in LG9 and LG23 and for survival time in LG6 and LG23. The analysis of the total data set identified an additional significant QTL for resistance and survival time in LG3 with the LR method. Significant association between disease resistance‐related traits and genotypes was detected for several markers, a single one explaining up to 22% of the phenotypic variance. Obtained results will be essential to identify candidate genes for resistance and to apply them in marker‐assisted selection programs to improve turbot production.     

Genome-wide linkage mapping of yield-related traits in three Chinese bread wheat populations using high-density SNP markers

Key message

We identified 21 new and stable QTL, and 11 QTL clusters for yield-related traits in three bread wheat populations using the wheat 90 K SNP assay.

Abstract

Identification of quantitative trait loci (QTL) for yield-related traits and closely linked molecular markers is important in order to identify gene/QTL for marker-assisted selection (MAS) in wheat breeding. The objectives of the present study were to identify QTL for yield-related traits and dissect the relationships among different traits in three wheat recombinant inbred line (RIL) populations derived from crosses Doumai?×?Shi 4185 (D?×?S), Gaocheng 8901?×?Zhoumai 16 (G?×?Z) and Linmai 2?×?Zhong 892 (L?×?Z). Using the available high-density linkage maps previously constructed with the wheat 90 K iSelect single nucleotide polymorphism (SNP) array, 65, 46 and 53 QTL for 12 traits were identified in the three RIL populations, respectively. Among them, 34, 23 and 27 were likely to be new QTL. Eighteen common QTL were detected across two or three populations. Eleven QTL clusters harboring multiple QTL were detected in different populations, and the interval 15.5–32.3 cM around the Rht-B1 locus on chromosome 4BS harboring 20 QTL is an important region determining grain yield (GY). Thousand-kernel weight (TKW) is significantly affected by kernel width and plant height (PH), whereas flag leaf width can be used to select lines with large kernel number per spike. Eleven candidate genes were identified, including eight cloned genes for kernel, heading date (HD) and PH-related traits as well as predicted genes for TKW, spike length and HD. The closest SNP markers of stable QTL or QTL clusters can be used for MAS in wheat breeding using kompetitive allele-specific PCR or semi-thermal asymmetric reverse PCR assays for improvement of GY.

     

Genetic diversity and association mapping in a collection of selected Chinese soybean accessions based on SSR marker analysis

For broadening the narrow genetic base of modern soybean cultivars, 159 accessions were selected from the Chinese soybean collection which contained at least one of seven important agronomic traits: resistance to soybean cyst nematode (SCN) or soybean mosaic virus (SMV), tolerance to salt, cold, or drought, high seed oil content or high protein content. Genetic diversity evaluation using 55 microsatellite loci distributed across the genome indicated that a large amount of genetic diversity (0.806) and allelic variation (781) were conserved in this selected set, which captured 65.6% of the alleles present in Chinese soybean collection (1,863 accessions). On average, 9.4 rare alleles (frequency <5%) per locus were present, which were highly informative. Using model-based Bayesian clustering in STRUCTURE we distinguished four main clusters and a set of accessions with admixed ancestry. The four clusters reflected different geographic regions of origin of the accessions. Since the clusters were also clearly different with respect to the seven agronomic traits, the inferred population structure was introduced when association analysis was conducted. A total of 21 SSR markers on 16 chromosomes were identified as significantly (P < 0.01) associated with high oil content (6), high protein content (1), drought tolerance (5), SCN resistance (6) and SMV resistance (3). Twelve of these markers were located in or near previously identified quantitative trait loci (QTL). The results for both genetic relationship and trait-related markers will be useful for effective conservation and utilization of soybean germplasm.     

Two consensus quantitative trait loci clusters controlling anthesis–silking interval, ear setting and grain yield might be related with drought tolerance in maize

Unravelling the molecular basis of drought tolerance will provide novel opportunities for improving crop yield under water-limited conditions. The present study was conducted to identify quantitative trait loci (QTLs) controlling anthesis–silking interval (ASI), ear setting percentage (ESP) and grain yield (GY). The mapping population included 234 F₂ plants derived from the cross X178 (drought tolerant) × B73 (drought susceptible). The corresponding F_2:3 progenies, along with their parents, were evaluated for the above-mentioned traits under both well-watered and water-stressed field conditions in three different trials carried out in central and southern China. Interval mapping and composite interval mapping identified 45 and 65 QTLs for the investigated traits, respectively. Two QTL clusters influencing ASI and ESP on chromosomes 1 (bin 1.03) and 9 (bins 9.03–9.05) were identified in more than two environments, showing sizeable additive effects and contribution to phenotypic variance; these two QTL clusters influenced GY only in one environment. No significant interaction was detected between the two genomic regions. A comparative analysis of these two QTL clusters with the QTLs controlling maize drought tolerance previously described in three mapping populations confirmed and extended their relevance for marker-assisted breeding to improve maize production under water-limited conditions.     

Transfer and mapping of the heat tolerance component traits of <Emphasis Type="Italic">Aegilops speltoides</Emphasis> in tetraploid wheat <Emphasis Type="Italic">Triticum durum</Emphasis>

Aegilops speltoides is an important genetic resource for wheat improvement and has high levels of heat tolerance. A heat-tolerant accession of Ae. speltoides pau3809 was crossed with Triticum durum cv. PDW274, and BC₂F_4-6 backcross introgression lines (BILs) were developed, phenotyped for important physiological traits, genotyped using SSR markers and used for mapping the QTL governing heat tolerance component traits. A set of 90 BILs was selected from preliminary evaluation of a broader set of 262 BILs under heat stress. Phenotyping was conducted for physiological traits such as cell membrane thermostability, chlorophyll content, acquired thermotolerance, canopy temperature and stay green. Much variation for these traits was observed in random as well as selected sets of BILs, and comparison of the BILs with the recurrent parent showed improvement for these traits under normal as well as heat stress conditions, indicating that introgressions from Ae. speltoides might have led to the improvement in the heat tolerance potential of the BILs. Introgression profiling of the 90 BILs using SSR markers identified Ae. speltoides introgression on all the 14 chromosomes with introgressions observed on A as well as B genome chromosomes. QTL mapping identified loci for various heat tolerance component traits on chromosomes 2B, 3A, 3B, 5A, 5B and 7A at significant LOD scores and with phenotypic contributions varying from 11.1 to 28.7 % for different traits. The heat-tolerant BILs and QTL reported in the present study form a potential resource that can be used for wheat germplasm enhancement for heat stress tolerance.     

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.     

Quantitative trait loci for body weight, condition factor and age at sexual maturation in Arctic charr (Salvelinus alpinus): comparative analysis with rainbow trout (Oncorhynchus mykiss) and Atlantic salmon (Salmo salar)

In salmonid fishes, life-history changes may often be coupled to early individual growth trajectories. We identified quantitative trait loci (QTL) for body weight (BW), condition factor (K) and age at sexual maturation (MT) in two full-sib families of Arctic charr (Salvelinus alpinus) to ascertain if QTL for MT were confounded with BW QTL intervals. Three significant QTL for BW, three QTL for MT and one significant QTL for K were identified. A BW QTL with major effect was localized to linkage group 8 (AC-8) and explained more than 34% of the phenotypic variation. Markers on AC-8 have previously been identified as being associated with variation in fork length and BW in this species. Similarly, a major QTL (PEV = 23%) with an influence on the female MT was localized to AC-23. Some of these regions are homologous to those in the genomes of rainbow trout (Oncorhynchus mykiss) and Atlantic salmon (Salmo salar), where similar QTL effects have been detected. Our results also suggest the conservation of MT QTL on the homeologous linkage group pair AC-3/24 in Arctic charr. We further identified chromosomal regions that harbor QTL for multiple traits. In particular, markers on AC-4, -20 and -36 had detectable QTL for all traits studied. Significant MT QTL detected on AC-23, -24, and -27 were autonomous of any BW QTL regions, suggesting that the regulation of MT may be more independent of BW control within this species than in other species of salmonids.     

Multi-trait evolution in a cave fish, Astyanax mexicanus

SUMMARY When surface species colonize caves, a characteristic suite of traits eventually evolves over time, regardless of species. The genetic basis of the inevitable appearance of these very similar phenotypes was investigated through quantitative trait loci (QTL) mapping of 12 traits that differ significantly between the recently evolved (<1 Myr). Mexican cave tetra and its surface conspecific. The traits were a representative set, including eye size, pigment cell numbers, chemical sensitivity, body and skull morphology, standard length, and metabolism. We used both single- and multi-trait models for QTL mapping. QTL effects of these traits were significantly clustered in the genome. We mapped 13 regions in the genome with QTL effects on from three to nine traits. These clusters could be multigenic or could represent single locus with pleiotropic alleles. Given the relatively short time available to construct clusters from unlinked genes through genomic rearrangement, and the counterintuitive polarities of some of the substitution effects, we argue that at least some of the clusters must have a pleiotropic basis.