Exercise Capacity and Response to Training Quantitative Trait Loci in a NZW X 129S1 Intercross and Combined Cross Analysis of Inbred Mouse Strains

Genetic factors determining exercise capacity and the magnitude of the response to exercise training are poorly understood. The aim of this study was to identify quantitative trait loci (QTL) associated with exercise training in mice. Based on marked differences in training responses in inbred NZW (-0.65 ± 1.73 min) and 129S1 (6.18 ± 3.81 min) mice, a reciprocal intercross breeding scheme was used to generate 285 F₂ mice. All F₂ mice completed an exercise performance test before and after a 4-week treadmill running program, resulting in an increase in exercise capacity of 1.54 ± 3.69 min (range = -10 to +12 min). Genome-wide linkage scans were performed for pre-training, post-training, and change in run time. For pre-training exercise time, suggestive QTL were identified on Chromosomes 5 (57.4 cM, 2.5 LOD) and 6 (47.8 cM, 2.9 LOD). A significant QTL for post-training exercise capacity was identified on Chromosome 5 (43.4 cM, 4.1 LOD) and a suggestive QTL on Chromosomes 1 (55.7 cM, 2.3 LOD) and 8 (66.1 cM, 2.2 LOD). A suggestive QTL for the change in run time was identified on Chromosome 6 (37.8 cM, 2.7 LOD). To identify shared QTL, this data set was combined with data from a previous F₂ cross between B6 and FVB strains. In the combined cross analysis, significant novel QTL for pre-training exercise time and change in exercise time were identified on Chromosome 12 (54.0 cM, 3.6 LOD) and Chromosome 6 (28.0 cM, 3.7 LOD), respectively. Collectively, these data suggest that combined cross analysis can be used to identify novel QTL and narrow the confidence interval of QTL for exercise capacity and responses to training. Furthermore, these data support the use of larger and more diverse mapping populations to identify the genetic basis for exercise capacity and responses to training.     

Development of a composite map in Vicia faba,breeding applications and future prospects

A composite map of the Vicia faba genome based on morphological markers, isozymes, RAPDs, seed protein genes and microsatellites was constructed. The map incorporates data from 11 F₂ families for a total of 654 individuals all sharing the common female parent Vf 6. The integrated map is arranged in 14 major linkage groups (five of which were located in specific chromosomes). These linkage groups include 192 loci and cover 1,559 cM with an overall average marker interval of 8 cM. By joining data of a new F₂ population segregating for resistance to ascochyta, broomrape and others traits of agronomic interest, have been saturated new areas of the genome. The combination of trisomic segregation, linkage analysis among loci from different families with a recurrent parent, and the analysis of new physically located markers, has allowed the establishment of the present status of the V. faba map with a wide coverage. This map provides an efficient tool in breeding applications such as disease-resistance mapping, QTL analyses and marker-assisted selection.Communicated by J.W. Snape     

Restriction fragment length polymorphism analysis of loci associated with disease resistance genes and developmental traits in Pisum sativum L.

An F₂ population of pea (Pisum sativum L.) consisting of 174 plants was analysed by restriction fragment length polymorphism (RFLP) and random amplified polymorphic DNA (RAPD) techniques. Ascochyta pisi race C resistance, plant height, flowering earliness and number of nodes were measured in order to map the genes responsible for their variation. We have constructed a partial linkage map including 3 morphological character genes, 4 disease resistance genes, 56 RFLP loci, 4 microsatellite loci and 2 RAPD loci. Molecular markers linked to each resistance gene were found: Fusarium wilt (6 cM from Fw), powdery mildew (11 cM from er) and pea common Mosaic virus (15 cM from mo). QTLs (quantitative traits loci) for Ascochyta pisi race C resistance were mapped, with most of the variation explained by only three chromosomal regions. The QTL with the largest effect, on chromosome 4, was also mapped using a qualitative, Mendelian approach. Another QTL displayed a transgressive segregation, i.e. the parental line that was susceptible to Ascochyta blight had a resistance allele at this QTL. Analysis of correlations between developmental traits in terms of QTL effects and positions suggested a common genetic control of the number of nodes and earliness, and a loose relationship between these traits and height.     

Fine mapping of a major locus on Chromosome 10 for exploratory and fear-like behavior in mice

Advanced intercross lines (AIL) and interval–specific congenic strains (ISCS) were used to fine map previously coarsely defined quantitative trait loci (QTL) on Chromosomes 1,10, and 19, influencing behaviors in the open Field (OF) and light–dark (LD) paradigms in mice. F₁₂(A × B) AIL mice (N = 1130) were phenotyped, genotyped, and mapped. The ISCS were studied only in the telomeric Chromosome 10 region of interest, containing the exploratory and excitability QTL1 (Exq1). The Chromosome 10 Exq1 and Chromosome 19 Exq4 loci mapped robustly in the AIL. The most significant QTL findings (2.0 LOD score intervals; peak; LOD score) came from the TD15 and LD transitions traits, yielding estimated intervals of 2.2 cM for Exq1 (71.3–73.5 cM; peak 72.3 cM; LOD 11.9) and 9.0 cM for Exq4 (29.0–38.2 cM; peak 34 cM; LOD 4.2). The replicated QTLs on Chromosome 1 failed to map in this AIL population. The ISCS data confirmed Exq1 loci in general. However, the ISCS data were complex and less definitive for localizing the Exq1 loci. These exploratory and fear-like behaviors result from inheriting “many small things,” namely, QTL explaining 2%–7% of the phenotypic variance. These results highlight the challenges of positionally cloning loci of small effect for complex traits. In particular, fine-mapping success may depend on the genetic architecture underlying complex traits.Shumin Zhang, Yigong Lou and Howard Gershenfeld contributed equally to this work. Abbreviations: ROI, Region of Interest; RI, recombinant inbred; AIL, advanced intercross line; ISCS, Interval-specific congenic strains; Sqrt, square root; QTL, quantitative trait loci; OF, open field; LOD, likelihood of the odds ratio score; Tde1, traveled distance epoch 1; TDe3, traveled distance epoch 3; TD15, traveled distance during 15 min; VM15, vertical movements during 15 min ; LD, light–dark transitions; AvgCtrT, average center time; Chr, chromosome; Exq, exploratory and excitability QTL.     

Systems genetic analysis of binge-like eating in a C57BL/6J x DBA/2J-F2 cross

Binge eating is a heritable trait associated with eating disorders and refers to the rapid consumption of a large quantity of energy-dense food that is, associated with loss of control and negative affect. Binge eating disorder is the most common eating disorder in the United States; however, the genetic basis is unknown. We previously identified robust mouse inbred strain differences between C57BL/6J and DBA/2J in binge-like eating of sweetened palatable food in an intermittent access, conditioned place preference paradigm. To map the genetic basis of changes in body weight and binge-like eating (BLE) and to identify candidate genes, we conducted quantitative trait locus (QTL) analysis in 128 C57BL/6J x DBA/2J-F2 mice combined with PheQTL and trait covariance analysis in GeneNetwork2 using legacy BXD-RI trait datasets. We identified a QTL on Chromosome 18 influencing changes in body weight across days in females (log of the odds [LOD] = 6.3; 1.5-LOD: 3–12 cM) that contains the candidate gene Zeb1. We also identified a sex-combined QTL influencing initial palatable food intake on Chromosome 5 (LOD = 5.8; 1.5-LOD: 21–28 cM) that contains the candidate gene Lcorl and a second QTL influencing escalated palatable food intake on Chromosome 6 in males (LOD = 5.4; 1.5-LOD: 50–59 cM) that contains the candidate genes Adipor2 and Plxnd1. Finally, we identified a suggestive QTL in females for slope of BLE on distal Chromosome 18 (LOD = 4.1; p = 0.055; 1.5-LOD: 23–35 cM). Future studies will use BXD-RI strains to fine map loci and support candidate gene nomination for gene editing.     

Genetic mapping of the athymic nude (RNU) locus in the rat to a region on Chromosome 10

The nude trait in the rat is transmitted in an autosomal recessive manner and is associated with thymic aplasia, T-cell deficiency, and hairlessness. Congenic rats homozygous for the RNU (Rowett nude) locus are important models in the study of inflammatory disease, tumor growth, and transplant rejection. The RNU locus has not been previously mapped, and the nature of the gene product is unknown. To determine the map location of this gene, a single F344.rnu/rnu (athymic nude congenic Fischer rat) male congenic rat was bred with 3 LEW/N (NIH stock Lewis rat) female rats to produce F₁ progeny. Twelve F₁ brother-sister breeding pairs were established. Forty-nine phenotypically nude F₂ offspring (198 total) were obtained. Linkage analysis done on F₂ DNA revealed highly significant cosegregation between the nude phenotype and eight polymorphic markers located on Chromosome (Chr) 10. The tightest linkages were with: MYH3 (embryonic, skeletal myosin heavy chain) and SHBG (sex hormone-binding globulin), giving 2 point lod scores of 20.2, and 20.0, respectively. The map order and map distances, determined by multipoint linkage calculations, were: RR24-(16.1 cM)-MYH3-(3.5 cM)-SHBG-(4.7 cM)-RNU-(11.9 cM)-F16F2-(24.1 cM)-CLATP (citrate lyase ATPase)-(2.4 cM)-ACE (angiotensin converting enzyme)/PPY (pancreatic polypeptide)-(14.1 cM)-RR1023. The position of the RNU locus in the rat corresponds closely with that of the recently reported nu locus in the mouse. This finding suggests that the nude phenotype in the rat and the mouse arise from defects in homologous genes.     

Genetic linkage analysis of X-ray hypersensitivity in the LEC mutant rat

The LEC rat has been reported to exhibit X-ray hypersensitivity and deficiency in DNA double-strand break (DSB) repair. The present study was performed to map the locus responsible for this phenotype, the xhs (X-ray hypersensitivity), as the first step in identifying the responsible gene. Analysis of the progeny of (BN × LEC)F₁× LEC backcrosses indicated that the X-ray hypersensitive phenotype was controlled by multiple genetic loci in contrast to the results reported previously. Quantitative trait loci (QTL) linkage analysis revealed two responsible loci located on Chromosomes (Chr) 4 and 1. QTL on Chr 4 exhibited very strong linkage to the X-ray hypersensitive phenotype, while QTL on Chr 1 showed weak linkage. The Rad52 locus, mutation of which results in hypersensitivity to ionizing radiation and impairment of DNA DSB repair in yeast, was reported to be located on the synteneic regions of mouse Chr 6 and human Chr 12. However, mapping of the rat Rad52 locus indicated that it was located 23 cM distal to the QTL on Chr 4. Furthermore, none of the radio-sensitivity-related loci mapped previously in the rat chromosome were identical to the QTL on Chrs 4 and 1 in the LEC rat. Thus, it seems that X-ray hypersensitivity in the LEC rat is caused by mutation(s) in as-yet-undefined genes. Received: 14 February 2000 / Accepted: 17 May 2000     

Genetic mapping and QTL analysis for yield and agronomic traits with an F2:3 population derived from a waxy corn × sweet corn cross

We constructed a framework map using SSR markers in the F₂ population derived from a cross between a waxy corn inbred line and a sweet corn inbred line. We constructed a genetic linkage map of the F_2:3 population employing 295 SSR markers on 158 F₂ individuals produced from the cross. The map comprised a total genomic length of 2,626.5 cM in 10 linkage groups and an average distance between markers of 8.9 cM. The number of loci per linkage group ranged from 27 (chr. 5) to 34 (chr. 7). The genetic distance per linkage group ranged from 213.6 cM (chr. 10) to 360.6 cM (chr. 2). Χ ² tests revealed that 254 markers (86.1 %) distributed over all 10 chromosomes exhibited a Mendelian segregation ratio of 1:2:1. A total of 14 quantitative trait loci (QTLs) for days to silking (DTS), plant height (PH), ear height (EH), ear height ratio (ER), ear length (L-ear), and setted ear length (L-sear) were found in the 158 F₂ progeny. They were mapped to chromosomes 1, 2, 3, 7, 8, and 10. Among them, one QTL was associated with DTS, three with PH, six with EH, one with ER, two with L-ear, and one QTL was related to L-sear. In our study, we found that four QTLs: qDTS1, qEH1a, qEH1b, and qPH1, were clustered between umc2390 and umc1603 on chromosome 1. These new QTLs identified by the present study could serve as useful molecular markers in selecting for yield and agronomic traits in maize. The results of this study may improve the identification and characterization of genes responsible for yield and agronomic traits in waxy corn and sweet corn.     

Linkage map and congenic strains to localize blood pressure QTL on rat Chromosome 10

Our purposes were to develop a linkage map for rat Chromosome (Chr) 10, using chromosome-sorted DNA, and to construct congenic strains to localize blood pressure quantitative trait loci (QTL) on Chr 10 with the map. The linkage mapping panel consisted of three F₂ populations totaling 418 rats. Thirty-two new and 29 known microsatellite markers were placed on the map, which spanned 88.9 centiMorgans (cM). The average distance between markers was 1.46 cM. No markers were separated by more than 6.8 cM. Four congenic strains were constructed by introgressing various segments of Chr 10 from the Milan normotensive strain (MNS) onto the background of the Dahl salt-sensitive (S) strain. A blood pressure QTL with a strong effect on blood pressure (35–42 mm Hg) when expressed on the S background was localized to a 31-cM region between D10Mco6 and D10Mcol. The region does not include the locus for inducible nitric oxide synthase (Nos2), which had been considered to be a candidate locus for the QTL. Received: 25 September 1996 / Accepted: 9 November 1996     

Next Generation Mapping of Enological Traits in an F2 Interspecific Grapevine Hybrid Family

In winegrapes (Vitis spp.), fruit quality traits such as berry color, total soluble solids content (SS), malic acid content (MA), and yeast assimilable nitrogen (YAN) affect fermentation or wine quality, and are important traits in selecting new hybrid winegrape cultivars. Given the high genetic diversity and heterozygosity of Vitis species and their tendency to exhibit inbreeding depression, linkage map construction and quantitative trait locus (QTL) mapping has relied on F₁ families with the use of simple sequence repeat (SSR) and other markers. This study presents the construction of a genetic map by single nucleotide polymorphisms identified through genotyping-by-sequencing (GBS) technology in an F₂ mapping family of 424 progeny derived from a cross between the wild species V. riparia Michx. and the interspecific hybrid winegrape cultivar, ‘Seyval’. The resulting map has 1449 markers spanning 2424 cM in genetic length across 19 linkage groups, covering 95% of the genome with an average distance between markers of 1.67 cM. Compared to an SSR map previously developed for this F₂ family, these results represent an improved map covering a greater portion of the genome with higher marker density. The accuracy of the map was validated using the well-studied trait berry color. QTL affecting YAN, MA and SS related traits were detected. A joint MA and SS QTL spans a region with candidate genes involved in the malate metabolism pathway. We present an analytical pipeline for calling intercross GBS markers and a high-density linkage map for a large F₂ family of the highly heterozygous Vitis genus. This study serves as a model for further genetic investigations of the molecular basis of additional unique characters of North American hybrid wine cultivars and to enhance the breeding process by marker-assisted selection. The GBS protocols for identifying intercross markers developed in this study can be adapted for other heterozygous species.     

QTL Mapping for Frond Length and Width in Laminaria japonica Aresch (Laminarales, Phaeophyta) Using AFLP and SSR Markers

In Laminaria japonica Aresch breeding practice, two quantitative traits, frond length (FL) and frond width (FW), are the most important phenotypic selection index. In order to increase the breeding efficiency by integrating phenotypic selection and marker-assisted selection, the first set of QTL controlling the two traits were determined in F₂ family using amplified fragment length polymorphism (AFLP) and simple sequence repeat (SSR) markers. Two prominent L. japonicas inbred lines, one with “broad and thin blade” characteristics and another with “long and narrow blade” characteristics, were applied in the hybridization to yield the F₂ mapping population with 92 individuals. A total of 287 AFLP markers and 11 SSR markers were used to construct a L. japonica genetic map. The yielded map was consisted of 28 linkage groups (LG) named LG1 to LG28, spanning 1,811.1 cM with an average interval of 6.7 cM and covering the 82.8% of the estimated genome 2,186.7 cM. While three genome-wide significant QTL were detected on LG1 (two QTL) and LG4 for “FL,” explaining in total 42.36% of the phenotypic variance, two QTL were identified on LG3 and LG5 for the trait “FW,” accounting for the total of 36.39% of the phenotypic variance. The gene action of these QTL was additive and partially dominant. The yielded linkage map and the detected QTL can provide a tool for further genetic analysis of two traits and be potential for maker-assisted selection in L. japonica breeding.     

Investigation of a QTL region for loin eye area and fatness on pig Chromosome 1

Previously, quantitative trait loci (QTL) for tenth-rib backfat (TENTHRIB) and loin eye area (LEA) were identified on pig Chromosome 1 (SSC 1) near microsatellite S0008 from a three-generation Berkshire × Yorkshire cross (BY). This work attempted to refine these QTL positions and identify genes associated with these QTL. Genotypes of BY (n = 555) were determined by PCR-RFLP or PCR tests for 13 polymorphisms identified in BY F₀ individuals for candidate genes, BAC end sequences, and genomic clones. Using least-squares regression interval mapping, the LEA QTL was estimated at S0008; the TENTHRIB QTL position was shifted approximately 1 cM downstream from S0008. Of the genes/sequences mapped in the QTL region, CL349415 was significantly associated with TENTHRIB (p = 0.02) and solute carrier family 2, member 12 (SLC2A12) was significantly associated with LEA (p = 0.02). These results suggest that the gene(s) responsible for the LEA and TENTHRIB QTL effects are tightly linked to S0008 or that the high informativeness of S0008 relative to surrounding markers is influencing the QTL position estimates. In addition, janus kinase 2 (JAK2) was mapped to a suggestive LEA QTL region and showed association with LEA (p = 0.009), fatness, color, and pH traits in BY.     

Quantitative trait locus effects and environmental interaction in a sample of North American barley germ plasm

Quantitative trait locus (QTL) and QTL x environment (E) interaction effects for agronomic and malting quality traits were measured using a 123-point linkage map and multi-environment phenotype data from an F₁-derived doubled haploid population of barley (Hordeum vulgare). The QTL × E interactions were due to differences in magnitude of QTL effects. Highly significant QTL effects were found for all traits at multiple sites in the genome. Yield QTL peaks and support intervals often coincided with plant height and lodging QTL peaks and support intervals. QTL were detected in the vicinity of a previously mapped Mendelian maturity locus and known function probes for- and-amylase genes. The average map density (9.6 cM) should be adequate for molecular marker-assisted selection, particularly since there were few cases of alternative favorable alleles for different traits mapping to the same or adjacent intervals.Oreg Agric Exp Stn J No. 10150     

QTL mapping for fiber quality traits across multiple generations and environments in upland cotton

Identification of quantitative trait loci (QTL) for fiber quality traits that are stable across multiple generations and environments could facilitate marker-assisted selection for improving cotton strains. In the present study, F₂, F_2:3, and recombinant inbred lines (RILs, F _6:8 ) populations derived from an upland cotton (Gossypium hirsutum L.) cross between strain 0-153, which has excellent fiber quality, and strain sGK9708, a commercial transgenic cultivar, were constructed for QTL tagging of fiber quality. We used 5,742 simple sequence repeat primer pairs to screen for polymorphisms between the two parent strains. Linkage maps of F₂ and RILs were constructed, containing 155 and 190 loci and with a total map distance of 959.4 centimorgans (cM) and 700.9?cM, respectively. We screened fiber quality QTL across multiple generations and environments through composite interval mapping of fiber quality data. Specifically, we studied F₂ and F_2:3 family lines from Anyang (Henan Province) in 2003 and 2004 and RILs in Anyang in 2007 and Anyang, Quzhou (Hebei Province), and Linqing (Shandong Province) in 2008. We identified 50 QTL for fiber quality: 10 for fiber strength, 10 for fiber length, 10 for micronaire, eight for fiber uniformity, and 12 for fiber elongation. Nine of these fiber quality QTL were identified in F₂, F_2:3 and RILs simultaneously. Two QTL for fiber strength on chromosomes C7 and C25 were detected in all three generations and all four environments and explained 16.67?C27.86% and 9.43?C21.36% of the phenotypic variation, respectively. These stable QTL for fiber quality traits could be used for marker assisted selection.     

Generation and exploration of a dense genetic map in a region of a QTL affecting corpora lutea in a Meishan × Yorkshire cross

Previously genomic scans revealed quantitative trait loci (QTL) on porcine Chromosome 8 (SSC8) as significantly affecting the number of corpora lutea (CL) in swine. In one study, statistical evidence for the putative QTL was found in the chromosomal region defined by the microsatellites (MS) SW205, SW444, SW206, and SW29. A Yeast Artificial Chromosome library was screened by using the corresponding primers for clones containing these MS by PCR. From five positive YAC clones, 10 additional MS were isolated and mapped to SSC8 with the INRA-University of Minnesota porcine Radiation Hybrid (IMpRH) panel. The genetic map position of the QTL has been refined by addition of these 10 markers. The QTL evaluation included pedigrees of F₂-intercross Meishan × Yorkshire design, with phenotypic data of 108 F₂ female offspring and genotypic data for 29 MS markers on SSC8. The analysis was performed by using the least squares regression method. The calculated QTL effect for CL obtained by the multilocus least squares method showed a maximum test statistic (F value = 13.98) at position 99 cM between three MS derived from YACs containing SW205 and SW1843 spanning an interval of 7.1 cM. The point-wise (nominal) P-value was 5.21 × 10⁻⁶ corresponding to a genome-wide P-value of 0.009. The additive QTL effect explained 17.4% of the phenotypic variance. Received: 23 December 2000 / Accepted: 07 May 2001     

Quantitative trait locus analysis of circulating adhesion molecules in hyperlipidemic apolipoprotein E-deficient mice

Circulating soluble adhesion molecules have been suggested as useful markers to predict several clinical conditions such as atherosclerosis, type 2 diabetes, obesity, and hypertension. To determine genetic factors influencing plasma levels of soluble vascular cell adhesion molecule-1 (VCAM-1) and P-selectin, quantitative trait locus (QTL) analysis was performed on an intercross between C57BL/6J (B6) and C3H/HeJ (C3H) mouse strains deficient in apolipoprotein E-deficient (apoE^−/−). Female F₂ mice were fed a western diet for 12 weeks. One significant QTL, named sVcam1 (71 cM, LOD 3.9), on chromosome 9 and three suggestive QTLs on chromosomes 5, 13 and 15 were identified to affect soluble VCAM-1 levels. Soluble P-selectin levels were controlled by one significant QTL, named sSelp1 (8.5 cM, LOD 3.4), on chromosome 16 and two suggestive QTLs on chromosomes 10 and 13. Both adhesion molecules showed significant or an apparent trend of correlations with body weight, total cholesterol, and LDL/VLDL cholesterol levels in the F₂ population. These results indicate that plasma VCAM-1 and P-selectin levels are complex traits regulated by multiple genes, and this regulation is conferred, at least partially, by acting on body weight and lipid metabolism in hyperlipidemic apoE^−/− mice. Zuobiao Yuan and Zhiguang Su contributed equally.     

Construction of a cucumber genetic linkage map with SRAP markers and location of the genes for lateral branch traits

Using SRAP (sequence-related amplified polymorphism) markers a genetic linkage map of cucumber was constructed with a population consisting of 138 F₂ individuals derived from a cross of the two cucumber lines, S06 and S52. In the survey of parental polymorphisms with 182 primer combinations, 64 polymorphism-revealing primer pairs were screened out, which generated totally 108 polymorphic bands with an average of 1.7 bands per primer pair and at most 6 bands from one primer pair. The constructed molecular linkage map included 92 loci, distributed in seven linkage groups and spanning 1164.2 cM in length with an average genetic distance of 12.6 cM between two neighboring loci. Based on this linkage map, the quantitative trait loci (QTL) for the lateral branch number (lbn) and the lateral branch average length (lbl) in cucumber were identified by QTLMapper1.6. A major QTL lbn1 located between ME11SA4B and ME5EM5 in LG2 could explain 10.63% of the total variation with its positively effecting allele from S06. A major QTL lbl1 located between DC1OD3 and DC1EM14 in LG2 could account for 10.38% of the total variation with its positively effecting allele from S₀₆.     

Quantitative trait loci segregating in crosses between New Hampshire and White Leghorn chicken lines: IV. Growth performance

Reciprocal crosses between the inbred lines New Hampshire (NHI) and White Leghorn (WL77) comprising 579 F₂ individuals were used to map QTL for body weight and composition. Here, we examine the growth performance until 20 weeks of age. Linkage analysis provided evidence for highly significant QTL on GGA1, 2, 4, 10 and 27 which had specific effects on early or late growth. The highest QTL effects, accounting for 4.6–25.6% of the phenotypic F₂ variance, were found on the distal region of GGA4 between 142 and 170 cM (F ≥ 13.68). The NHI QTL allele increased body mass by 141.86 g at 20 weeks. Using body weight as a covariate in the analysis of body composition traits provided evidence for genes in the GGA4 QTL region affecting fat mass independently of body mass. The QTL effect size differed between sexes and depended on the direction of cross. TBC1D1, CCKAR and PPARGC1A are functional candidate genes in the QTL peak region. Our study confirmed the importance of the distal GGA4 region for chicken growth performance. The strong effect of the GGA4 QTL makes fine mapping and gene discovery feasible.     

A genetic linkage map of water yam ( Dioscorea alata L.) based on AFLP markers and QTL analysis for anthracnose resistance

A genetic linkage map of the tetraploid water yam (Dioscorea alata L.) genome was constructed based on 469 co-dominantly scored amplified fragment length polymorphism (AFLP) markers segregating in an intraspecific F₁ cross. The F₁ was obtained by crossing two improved breeding lines, TDa 95/00328 as female parent and TDa 87/01091 as male parent. Since the mapping population was an F₁ cross between presumed heterozygous parents, marker segregation data from both parents were initially split into maternal and paternal data sets, and separate genetic linkage maps were constructed. Later, data analysis showed that this was not necessary and thus the combined markers from both parents were used to construct a genetic linkage map. The 469 markers were mapped on 20 linkage groups with a total map length of 1,233 cM and a mean marker spacing of 2.62 cM. The markers segregated like a diploid cross-pollinator population suggesting that the water yam genome is allo-tetraploid (2n = 4x = 40). QTL mapping revealed one AFLP marker E-14/M52-307 located on linkage group 2 that was associated with anthracnose resistance, explaining 10% of the total phenotypic variance. This map covers 65% of the yam genome and is the first linkage map reported for D. alata. The map provides a tool for further genetic analysis of traits of agronomic importance and for using marker-assisted selection in D. alata breeding programmes. QTL mapping opens new avenues for accumulating anthracnose resistance genes in preferred D. alata cultivars.     

Construction of the First High-Density Genetic Linkage Map and Analysis of Quantitative Trait Loci for Growth-Related Traits in <Emphasis Type="Italic">Sinonovacula constricta</Emphasis>

The razor clam (Sinonovacula constricta) is an important aquaculture species, for which a high-density genetic linkage map would play an important role in marker-assisted selection (MAS). In this study, we constructed a high-density genetic map and detected quantitative trait loci (QTLs) for Sinonovacula constricta with an F₁ cross population by using the specific locus amplified fragment sequencing (SLAF-seq) method. A total of 315,553 SLAF markers out of 467.71 Mreads were developed. The final linkage map was composed of 7516 SLAFs (156.60-fold in the parents and 20.80-fold in each F₁ population on average). The total distance of the linkage map was 2383.85 cM, covering 19 linkage groups with an average inter-marker distance of 0.32 cM. The proportion of gaps less than 5.0 cM was on average 96.90%. A total of 16 suggestive QTLs for five growth-related traits (five QTLs for shell height, six QTLs for shell length, three QTLs for shell width, one QTL for total body weight, and one QTL for soft body weight) were identified. These QTLs were distributed on five linkage groups, and the regions showed overlapping on LG9 and LG13. In conclusion, the high-density genetic map and QTLs for S. constricta provide a valuable genetic resource and a basis for MAS.