The candidate gene, Clock, localizes to a strong spawning time quantitative trait locus region in rainbow trout

We applied a candidate gene mapping approach to an existing quantitative trait loci (QTL) data set for spawning date in rainbow trout (Oncorynchus mykiss) to ascertain whether these genes could potentially account for any observed QTL effects. Several genes were chosen for their known or suspected roles in reproduction, circadian, or circannual timing, including salmon-type gonadotropin-releasing hormone 3A and 3B (GnRH3A and GnRH3B), Clock, Period1, and arylalkylamine N-acetlytransferase-1 and -2 (AANAT-1 and AANAT-2). Genes were sequenced, and polymorphisms were identified in parents of two rainbow trout mapping families, one of which was used previously to detect spawn timing QTL. Interval mapping was used to identify associations between genetic markers and spawning date effects. Using a genetic map that was updated with 574 genetic markers (775 total), we found evidence for 11 significant or suggestive QTL regions. Most QTL were only localized within one of the parents; however, a strong QTL region was identified in both female and male parents on linkage group RT-8 that explained 20% and 50% of trait variance, respectively. The Clock gene mapped to this region. Period1 mapped to a region in the female parent associated with a marginal effect (P = .056) on spawn timing. Other candidate genes were not associated with significant QTL effects.     

Altered placental expression of PAPPA2 does not affect birth weight in mice

Background  

Pregnancy-associated plasma protein A2 (PAPPA2) is an insulin-like growth factor binding protein (IGFBP) protease expressed in the placenta and upregulated in pregnancies complicated by pre-eclampsia. The mechanism linking PAPPA2 expression and pre-eclampsia and the consequences of altered PAPPA2 expression remain unknown. We previously identified PAPPA2 as a candidate gene for a quantitative trait locus (QTL) affecting growth in mice and in the present study examined whether this QTL affects placental PAPPA2 expression and, in turn, placental or embryonic growth.     

Mapping of a milk production quantitative trait locus to a 1.056 Mb region on bovine chromosome 5 in the Fleckvieh dual purpose cattle breed

Background

In a previous study in the Fleckvieh dual purpose cattle breed, we mapped a quantitative trait locus (QTL) affecting milk yield (MY1), milk protein yield (PY1) and milk fat yield (FY1) during first lactation to the distal part of bovine chromosome 5 (BTA5), but the confidence interval was too large for positional cloning of the causal gene. Our objective here was to refine the position of this QTL and to define the candidate region for high-throughput sequencing.

Methods

In addition to those previously studied, new Fleckvieh families were genotyped, in order to increase the number of recombination events. Twelve new microsatellites and 240 SNP markers covering the most likely QTL region on BTA5 were analysed. Based on haplotype analysis performed in this complex pedigree, families segregating for the low frequency allele of this QTL (minor allele) were selected. Single- and multiple-QTL analyses using combined linkage and linkage disequilibrium methods were performed.

Results

Single nucleotide polymorphism haplotype analyses on representative family sires and their ancestors revealed that the haplotype carrying the minor QTL allele is rare and most probably originates from a unique ancestor in the mapping population. Analyses of different subsets of families, created according to the results of haplotype analysis and availability of SNP and microsatellite data, refined the previously detected QTL affecting MY1 and PY1 to a region ranging from 117.962 Mb to 119.018 Mb (1.056 Mb) on BTA5. However, the possibility of a second QTL affecting only PY1 at 122.115 Mb was not ruled out.

Conclusion

This study demonstrates that targeting families segregating for a less frequent QTL allele is a useful method. It improves the mapping resolution of the QTL, which is due to the division of the mapping population based on the results of the haplotype analysis and to the increased frequency of the minor allele in the families. Consequently, we succeeded in refining the region containing the previously detected QTL to 1 Mb on BTA5. This candidate region contains 27 genes with unknown or partially known function(s) and is small enough for high-throughput sequencing, which will allow future detailed analyses of candidate genes.     

The genetic architecture of shoot branching in Arabidopsis thaliana: a comparative assessment of candidate gene associations vs. quantitative trait locus mapping

Association mapping focused on 36 genes involved in branch development was used to identify candidate genes for variation in shoot branching in Arabidopsis thaliana. The associations between four branching traits and moderate-frequency haplogroups at the studied genes were tested in a panel of 96 accessions from a restricted geographic range in Central Europe. Using a mixed-model association-mapping method, we identified three loci--MORE AXILLARY GROWTH 2 (MAX2), MORE AXILLARY GROWTH 3 (MAX3), and SUPERSHOOT 1 (SPS1)--that were significantly associated with branching variation. On the basis of a more extensive examination of the MAX2 and MAX3 genomic regions, we find that linkage disequilibrium in these regions decays within approximately 10 kb and trait associations localize to the candidate genes in these regions. When the significant associations are compared to relevant quantitative trait loci (QTL) from previous Ler x Col and Cvi x Ler recombinant inbred line (RIL) mapping studies, no additive QTL overlapping these candidate genes are observed, although epistatic QTL for branching, including one that spans the SPS1, are found. These results suggest that epistasis is prevalent in determining branching variation in A. thaliana and may need to be considered in linkage disequilibrium mapping studies of genetically diverse accessions.     

Comparative genetic analysis of a wheat seed dormancy QTL with rice and <Emphasis Type="Italic">Brachypodium</Emphasis> identifies candidate genes for ABA perception and calcium signaling

Wheat preharvest sprouting (PHS) occurs when seed germinates on the plant before harvest resulting in reduced grain quality. In wheat, PHS susceptibility is correlated with low levels of seed dormancy. A previous mapping of quantitative trait loci (QTL) revealed a major PHS/seed dormancy QTL, QPhs.cnl-2B.1, located on wheat chromosome 2B. A comparative genetic study with the related grass species rice (Oryza sativa L.) and Brachypodium distachyon at the homologous region to the QPhs.cnl-2B.1 interval was used to identify the candidate genes for marker development and subsequent fine mapping. Expressed sequence tags and a comparative mapping were used to design 278 primer pairs, of which 22 produced polymorphic amplicons that mapped to the group 2 chromosomes. Fourteen mapped to chromosome 2B, and ten were located in the QTL interval. A comparative analysis revealed good macrocollinearity between the PHS interval and 3 million base pair (mb) region on rice chromosomes 7 and 3, and a 2.7-mb region on Brachypodium Bd1. The comparative intervals in rice were found to contain three previously identified rice seed dormancy QTL. Further analyses of the interval in rice identified genes that are known to play a role in seed dormancy, including a homologue for the putative Arabidopsis ABA receptor ABAR/GUN5. Additional candidate genes involved in calcium signaling were identified and were placed in a functional protein association network that includes additional proteins critical for ABA signaling and germination. This study provides promising candidate genes for seed dormancy in both wheat and rice as well as excellent molecular markers for further comparative and fine mapping.     

Quantitative trait loci for the circadian clock in Neurospora crassa

Neurospora crassa has been a model organism for the study of circadian clocks for the past four decades. Among natural accessions of Neurospora crassa, there is significant variation in clock phenotypes. In an attempt to investigate natural allelic variants contributing to quantitative variation, we used a quantitative trait loci mapping approach to analyze three independent mapping populations whose progenitors were collected from geographically isolated locations. Two circadian clock phenotypes, free-running period and entrained phase, were evaluated in the 188 F(1) progeny of each mapping population. To identify the clock QTL, we applied two QTL mapping analyses: composite interval mapping (CIM) and Bayesian multiple QTL analysis (BMQ). When controlling false positive rates < or =0.05, BMQ appears to be the more sensitive of the two approaches. BMQ confirmed most of the QTL from CIM (18 QTL) and identified 23 additional QTL. While 13 QTL colocalize with previously identified clock genes, we identified 30 QTL that were not linked with any previously characterized clock genes. These are candidate regions where clock genes may be located and are expected to lead to new insights in clock regulation.     

Deficiency mapping of quantitative trait loci affecting longevity in Drosophila melanogaster

In a previous study, sex-specific quantitative trait loci (QTL) affecting adult longevity were mapped by linkage to polymorphic roo transposable element markers, in a population of recombinant inbred lines derived from the Oregon and 2b strains of Drosophila melanogaster. Two life span QTL were each located on chromosomes 2 and 3, within sections 33E-46C and 65D-85F on the cytological map, respectively. We used quantitative deficiency complementation mapping to further resolve the locations of life span QTL within these regions. The Oregon and 2b strains were each crossed to 47 deficiencies spanning cytological regions 32F-44E and 64C-76B, and quantitative failure of the QTL alleles to complement the deficiencies was assessed. We initially detected a minimum of five and four QTL in the chromosome 2 and 3 regions, respectively, illustrating that multiple linked factors contribute to each QTL detected by recombination mapping. The QTL locations inferred from deficiency mapping did not generally correspond to those of candidate genes affecting oxidative and thermal stress or glucose metabolism. The chromosome 2 QTL in the 35B-E region was further resolved to a minimum of three tightly linked QTL, containing six genetically defined loci, 24 genes, and predicted genes that are positional candidates corresponding to life span QTL. This region was also associated with quantitative variation in life span in a sample of 10 genotypes collected from nature. Quantitative deficiency complementation is an efficient method for fine-scale QTL mapping in Drosophila and can be further improved by controlling the background genotype of the strains to be tested.     

Genetic Evaluation of Candidate Genes for the Mom1 Modifier of Intestinal Neoplasia in Mice

As genetic mapping of quantitative trait loci (QTL) becomes routine, the challenge is to identify the underlying genes. This paper develops rigorous genetic tests for evaluation of candidate genes for a QTL, involving determination of allelic status in inbred strains and fine-structure genetic mapping. For the Mom1 modifier of intestinal adenomas caused by Apc(Min), these tests are used to evaluate two candidate genes: Pla2g2a, a secretory phospholipase, and Rap1GAP, a GTPase activating protein. Rap1GAP passes the first test but is excluded by a single fine-structure recombinant. Pla2g2a passes both tests and is a strong candidate for Mom1. Significantly, we also find that Apc(Min)-induced adenomas remain heterozygous for the Mom1 region, consistent with Mom1 acting outside the tumor lineage and encoding a secreted product.     

Molecular Dissection of a Genomic Region Governing Root Traits Associated with Drought Tolerance Employing a Combinatorial Approach of QTL Mapping and RNA-seq in Rice

Drought is considered as one of the major obstacles for progressive yield enhancement and stability in rice, especially in rain-fed conditions. Being a complex trait, drought is regulated by numerous quantitative trait loci (QTL), of which, however, very few underlying genes have been cloned. In the present investigation, we made an attempt to uncover the candidate gene(s) behind a major QTL, rdw8.1 governing drought tolerance traits viz., root dry weight and root length. The targeted QTL has been delimited to 366.75 kb from 10.17 Mb by QTL mapping in BC₁F₂ population. Further, the targeted region was delineated employing next-generation sequencing based RNA-seq. Based on the QTL mapping and RNA-seq approaches, the plausible candidate gene underlying the QTL region was identified as a wound inducible protein (LOC_Os08g08090). This gene can be of potential value to enhance the drought tolerance of the elite rice varieties through molecular breeding.     

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 .     

Vanaso is a candidate quantitative trait gene for Drosophila olfactory behavior

Most animals depend on olfaction for survival and procreation. Odor-guided behavior is a quantitative trait, with phenotypic variation due to multiple segregating quantitative trait loci (QTL). Despite its profound biological importance, the genetic basis of naturally occurring variation in olfactory behavior remains unexplored. Here, we mapped a single Drosophila QTL affecting variation in avoidance response to benzaldehyde, using a population of recombinant inbred lines. Deficiency complementation mapping resolved this region into one female- and one male-specific QTL. Subsequent quantitative complementation tests to all available mutations of positional candidate genes showed that the female-specific QTL failed to complement a P-element insertional mutation, l(3)04276. The P-element insertion was in the intron of a novel gene, Vanaso, which contains a putative guanylate binding protein domain, is highly polymorphic, and is expressed in the third antennal segment, the major olfactory organ of Drosophila. No expression was detected in the fly brain, suggesting that Vanaso plays a role in peripheral chemosensory processes rather than in central integration of olfactory information. QTL mapping followed by quantitative complementation tests to deficiencies and mutations is an effective strategy for gene discovery that allows characterization of effects of recessive lethal genes on adult phenotypes and here enabled identification of a candidate gene that contributes to sex-specific quantitative variation in olfactory behavior.     

Conditional QTL underlying resistance to late blight in a diploid potato population

A large number of quantitative trait loci (QTL) for resistance to late blight of potato have been reported with a "conventional" method in which each phenotypic trait reflects the cumulative genetic effects for the duration of the disease process. However, as genes controlling response to disease may have unique contributions with specific temporal features, it is important to consider the phenotype as dynamic. Here, using the net genetic effects evidenced at consecutive time points during disease development, we report the first conditional mapping of QTL underlying late blight resistance in potato under five environments in Peru. Six conditional QTL were mapped, one each on chromosome 2, 7 and 12 and three on chromosome 9. These QTL represent distinct contributions to the phenotypic variation at different stages of disease development. By comparison, when conventional mapping was conducted, only one QTL was detected on chromosome 9. This QTL was the same as one of the conditional QTL. The results imply that conditional QTL reflect genes that function at particular stages during the host-pathogen interaction. The dynamics revealed by conditional QTL mapping could contribute to the understanding of the molecular mechanism of late blight resistance and these QTL could be used to target genes for marker development or manipulation to improve resistance.     

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.     

QTL detection for forage quality and stem histology in four connected mapping populations of the model legume Medicago truncatula

Forage quality combines traits related to protein content and energy value. High-quality forages contribute to increase farm autonomy by reducing the use of energy or protein-rich supplements. Genetic analyses in forage legume species are complex because of their tetraploidy and allogamy. Indeed, no genetic studies of quality have been published at the molecular level on these species. Nonetheless, mapping populations of the model species M. truncatula can be used to detect QTL for forage quality. Here, we studied a crossing design involving four connected populations of M. truncatula. Each population was composed of ca. 200 recombinant inbred lines (RIL). We sought population-specific QTL and QTL explaining the whole design variation. We grew parents and RIL in a greenhouse for 2 or 3 seasons and analysed plants for chemical composition of vegetative organs (protein content, digestibility, leaf-to-stem ratio) and stem histology (stem cross-section area, tissue proportions). Over the four populations and all the traits, QTL were found on all chromosomes. Among these QTL, only four genomic regions, on chromosomes 1, 3, 7 and 8, contributed to explaining the variations in the whole crossing design. Surprisingly, we found that quality QTL were located in the same genomic regions as morphological QTL. We thus confirmed the quantitative inheritance of quality traits and tight relationships between quality and morphology. Our findings could be explained by a co-location of genes involved in quality and morphology. This study will help to detect candidate genes involved in quantitative variation for quality in forage legume species.     

Systematic analysis of <Emphasis Type="Italic">NPK1</Emphasis>-like genes in rice reveals a stress-inducible gene cluster co-localized with a quantitative trait locus of drought resistance

Phosphorylation by protein kinase is a ubiquitous key mechanism in translating external stimuli such as drought stress. NPK1 is a mitogen-activated protein kinase kinase kinase identified in Nicotiana tabacum and plays important roles in cytokinesis and auxin signaling transduction and responses to multiple stresses. Here we report the evolution, structure, and comprehensive expression profile of 21 NPK1-like genes in rice (Oryza sativa L.). Phylogenetic analysis of NPK1-like sequences in rice (OsNPKL), Arabidopsis, and other plants reveals that NPK1-like genes could be classified into three subgroups. Three OsNPKL gene clusters, located on chromosome 1 (OsNPKL1, 2, 3, and 4), 5 (OsNPKL14 and 15), and 10 (OsNPKL19 and 20), respectively, were identified in the rice genome. These clustered genes, which most likely evolved by tandem gene duplication, belong to the same phylogenetic subgroup, with similar genomic structures and conserved motifs in the kinase domain, which is unique to this subgroup. Expression analysis of OsNPKL genes under abiotic stresses suggests that the stress-responsive genes are mainly from the same subgroup. Especially interesting is that all the clustered genes are induced by drought, salt, or cold stress, and a few members are very strongly induced by drought. Some of the clustered genes are also induced by abscisic acid. The gene cluster on chromosome 1 is co-located with a quantitative trait locus (QTL) related to drought resistance. Although the drought-induced expression levels of the four genes in the cluster show no difference between the two parents used for QTL mapping, sequence variation in coding regions of the genes between the parents has provided some clues for further functional characterization of this gene cluster in abiotic stress tolerance in rice.     

Whole-Genome Quantitative Trait Locus Mapping Reveals Major Role of Epistasis on Yield of Rice

Although rice yield has been doubled in most parts of the world since 1960s, thanks to the advancements in breeding technologies, the biological mechanisms controlling yield are largely unknown. To understand the genetic basis of rice yield, a number of quantitative trait locus (QTL) mapping studies have been carried out, but whole-genome QTL mapping incorporating all interaction effects is still lacking. In this paper, we exploited whole-genome markers of an immortalized F₂ population derived from an elite rice hybrid to perform QTL mapping for rice yield characterized by yield per plant and three yield component traits. Our QTL model includes additive and dominance main effects of 1,619 markers and all pair-wise interactions, with a total of more than 5 million possible effects. The QTL mapping identified 54, 5, 28 and 4 significant effects involving 103, 9, 52 and 7 QTLs for the four traits, namely the number of panicles per plant, the number of grains per panicle, grain weight, and yield per plant. Most identified QTLs are involved in digenic interactions. An extensive literature survey of experimentally characterized genes related to crop yield shows that 19 of 54 effects, 4 of 5 effects, 12 of 28 effects and 2 of 4 effects for the four traits, respectively, involve at least one QTL that locates within 2 cM distance to at least one yield-related gene. This study not only reveals the major role of epistasis influencing rice yield, but also provides a set of candidate genetic loci for further experimental investigation.