QTL analysis of body weight and carcass body length traits in an F2 intercross between Landrace and Korean native pigs

Growth traits, such as body weight and carcass body length, directly affect productivity and economic efficiency in the livestock industry. We performed a genome‐wide linkage analysis to detect the quantitative trait loci (QTL) that affect body weight, growth curve parameters and carcass body length in an F₂ intercross between Landrace and Korean native pigs. Eight phenotypes related to growth were measured in approximately 1000 F₂ progeny. All experimental animals were subjected to genotypic analysis using 173 microsatellite markers located throughout the pig genome. The least squares regression approach was used to conduct the QTL analysis. For body weight traits, we mapped 16 genome‐wide significant QTL on SSC1, 3, 5, 6, 8, 9 and 12 as well as 22 suggestive QTL on SSC2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 16 and 17. On SSC12, we identified a major QTL affecting body weight at 140 days of age that accounted for 4.3% of the phenotypic variance, which was the highest test statistic (F‐ratio = 45.6 under the additive model, nominal P = 2.4 × 10^?11) observed in this study. We also showed that there were significant QTL on SSC2, 5, 7, 8, 9 and 12 affecting carcass body length and growth curve parameters. Interestingly, the QTL on SSC2, 3, 5, 6, 8, 9, 10, 12 and 17 influencing the growth‐related traits showed an obvious trend for co‐localization. In conclusion, the identified QTL may play an important role in investigating the genetic structure underlying the phenotypic variation of growth in pigs.     

A comparative study of the genetic bases of natural variation in tomato leaf,sepal, and petal morphology

In an effort to better understand the dramatic differences in vegetative and floral morphology that differentiate species within the genus Lycopersicon, quantitative trait loci (QTL) for leaflet and perianth size and shape characters were mapped in an interspecific F₂ population of tomato (Lycopersicon esculentum × L. pennellii). Thirty-six highly significant (P0.001) QTL were associated with 18 separate traits. QTL for correlated traits were generally not colocalized in the genome unless there was a clear codependence between the traits (e.g., organ length and area). Little or no overlap in QTL positioning between different organs was observed, suggesting that the genes determining the size and shape of leaflets, sepals, and petals are organ specific. Thus, while leaves are considered the developmental and evolutionary precursors to floral organs, genes acting late in development to determine certain aspects of morphology (namely shape and size) must have specialized to exert control over individual organs. Five of the leaflet-trait QTL map to analogous regions in the genome of eggplant, and therefore it appears there has been some conservation in the genes controlling leaf morphology within the Solanaceae.     

A large-sample QTL study in mice: III. Reproduction

Using lines of mice having undergone long-term selection for high and low growth, a large-sample (n 1000 F₂) experiment was conducted to gain further understanding of the genetic architecture of complex polygenic traits. Composite interval mapping on data from 10-week-old F₂ females (n=439) detected 15 quantitative trait loci (QTLs) on 5 chromosomes that influence reproduction traits characterized at day 16 of gestation. These QTL are broadly categorized into two groups: those where effects on the number of live fetuses (LF) were accompanied by parallel effects on the number of dead fetuses (DF), and those free of such undesirable effects. QTL for ovulation rate (OR) did not overlap with QTL for litter size, potentially indicating the importance of uterine capacity. Large dominance effects were identified for most QTL detected, and overdominance was also present. The QTL of largest effects were detected in regions of Chromosome 2, where large QTL effects for growth and fatness have also been found and where corroborating evidence from other studies exists. Considerable overlap between locations of QTL for reproductive traits and for growth traits corresponds well with the positive correlations usually observed among these sets of phenotypes. Some support for the relevance of QTL × genetic background interactions in reproduction was detected. Traits with low heritability demand considerably larger sample sizes to achieve effective power of QTL detection. This is unfortunate as traits with low heritability are among those that could most benefit from QTL-complemented breeding and selection strategies in food animal production.     

Genotype × diet interactions in mice predisposed to mammary cancer. I. Body weight and fat

High dietary fat intake and obesity may increase susceptibility to certain forms of cancer. To study the interactions of dietary fat, obesity, and metastatic mammary cancer, we created a population of F₂ mice cosegregating obesity QTL and the MMTV-PyMT transgene. We fed the F₂ mice either a very-high-fat or a matched-control-fat diet and measured growth, body composition, age at mammary tumor onset, tumor number and severity, and formation of pulmonary metastases. SNP genotyping across the genome facilitated analyses of QTL and QTL × diet interaction effects. Here we describe development of the F₂ population (n = 615) which resulted from a cross between the polygenic obesity model M16i and FVB/NJ-TgN (MMTV-PyMT)^634Mul, effects of diet on growth and body composition, and QTL and QTL × diet and/or gender interaction effects for growth and obesity-related phenotypes. We identified 38 QTL for body composition traits that were significant at the genome-wide 0.05 level, likely representing nine distinct loci after accounting for pleiotropic effects. QTL × diet and/or gender interactions were present at 15 of these QTL, indicating that such interactions play a significant role in defining the genetic architecture of complex traits such as body weight and obesity.     

Comparative mapping in F2∶3 and F6∶7 generations of quantitative trait loci for grain yield and yield components in maize

This study was conducted to compare maize quantitative trait loci (QTL) detection for grain yield and yield components in F₂₃ and F₆₇ recombinant inbred (RI) lines from the same population. One hundred and eighty-six F₆₇ RIs from a Mo17×H99 population were grown in a replicated field experiment and analyzed at 101 loci detected by restriction fragment length polymorphisms (RFLPs). Single-factor analysis of variance was conducted for each locus-trait combination to identify QTL. For grain yield, 6 QTL were detected accounting for 22% of the phenotypic variation. A total of 63 QTL were identified for the seven grain yield components with alleles from both parents contributing to increased trait values. Several genetic regions were associated with more than one trait, indicating possible linked and/or pleiotropic effects. In a comparison with 150 F₂₃ lines from the same population, the same genetic regions and parental effects were detected across generations despite being evaluated under diverse environmental conditions. Some of the QTL detected in the F₂₃ seem to be dissected into multiple, linked QTL in the F₆₇ generation, indicating better genetic resolution for QTL detection with RIs. Also, genetic effects at QTL are smaller in the F₆₇ generation for all traits.Abbreviations RFLPs Restriction fragment length polymorphisms - QTL quantitative trait loci - RIs recombinant inbreds Journal Paper no. J-16261 of the Iowa Agric and Home Economics Exp Stn Project no. 3134     

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     

Identification and validation of QTL for Sclerotinia midstalk rot resistance in sunflower by selective genotyping

Midstalk rot, caused by Sclerotinia sclerotiorum (Lib.) de Bary, is an important cause of yield loss in sunflower (Helianthus annuus L.). Objectives of this study were to: (1) estimate the number, genomic positions and genetic effects of quantitative trait loci (QTL) for resistance to midstalk rot in line TUB-5-3234, derived from an interspecific cross; (2) determine congruency of QTL between this line and other sources of resistance; and (3) make inferences about the efficiency of selective genotyping (SG) in detecting QTL conferring midstalk rot resistance in sunflower. Phenotypic data for three resistance (stem lesion, leaf lesion and speed of fungal growth) and two morphological (leaf length and leaf length with petiole) traits were obtained from 434 F₃ families from cross CM625 (susceptible) × TUB-5-3234 (resistant) under artificial infection in field experiments across two environments. The SG was applied by choosing the 60 most resistant and the 60 most susceptible F₃ families for stem lesion. For genotyping of the respective F₂ plants, 78 simple sequence repeat markers were used. Genotypic variances were highly significant for all traits. Heritabilities and genotypic correlations between resistance traits were moderate to high. Three to four putative QTL were detected for each resistance trait explaining between 40.8% and 72.7% of the genotypic variance ( ). Two QTL for stem lesion showed large genetic effects and corroborated earlier findings from the cross NDBLOS_sel (resistant) × CM625 (susceptible). Our results suggest that SG can be efficiently used for QTL detection and the analysis of congruency for resistance genes across populations.     

Quantitative trait loci for steady-state platelet count in mice

Platelet count in humans is a strongly genetically regulated trait, with approximately 85% of the interindividual variance in platelet numbers attributable to genetic factors. Inbred mouse strains also have strain-specific platelet count ranges. As part of a project to identify novel factors that regulate platelet count, we identified two inbred mouse strains, CBA/CaH and QSi5, with substantial differences in platelet count (mean values of 581 vs. 1062 × 10⁹/L). An F₂ intercross resource of 1126 animals was bred from these two parental strains for a genomewide scan for quantitative trait loci (QTL) for platelet count. QTL were identified on MMU1 (LOD 6.8, p < 0.0005) and MMU11 (LOD 11.2, p < 0.0005) by selectively genotyping animals from the extremes of the F₂ platelet count distribution. Three other QTL of suggestive statistical significance were also detected on MMU7, 13, and 17. It is noteworthy that no QTL were detected in the vicinity of the genes encoding thrombopoietin (Thpo), and its receptor (c-Mpl), both known to influence platelet production. Comparison of gene expression levels between the parental mouse strains by microarrays also showed little difference in the mRNA levels of these known candidate genes. These results represent the first published use of a genetic linkage-based approach in a mouse model toward the identification of genetic factors that regulate platelet count.     

Molecular marker-facilitated studies in an elite maize population: I. Linkage analysis and determination of QTL for morphological traits

Restriction fragment length polymorphisms (RFLPs) and one morphological marker were used to investigate quantitative trait loci (QTL) for morphological and physiological traits evaluated on 150 F₂₃ maize (Zea mays L.) lines derived from the cross of elite U.S. Corn Belt inbreds Mo17 and H99. F₂₃ lines were grown in a replicated experiment and evaluated for plant and ear heights and flowering traits. QTL were identified for each trait, and genetic effects were determined. Estimated gene action for the flowering traits was predominantly overdominance. Both parents contributed toward increased values for anthesis and silk emergence. QTL for increased plant and ear heights were usually contributed by the taller parent, Mo17. Estimated gene action for these traits was mainly partial to overdominance. QTL for plant height were located in the vicinity of loci defined by alleles with qualitative effects on plant height.     

QTL analyses of drought tolerance and growth for a Salix dasyclados × Salix viminalis hybrid in contrasting water regimes

Quantitative trait loci (QTL) for growth traits and water-use efficiency have been identified in two water regimes (normal and drought-treated) and for a treatment index. A tetraploid hybrid F₂ population originating from a cross between a Salix dasyclados clone (SW901290) and a Salix viminalis clone (Jorunn) was used in the study. The growth response of each individual including both above and below ground dry-matter production (i.e. shoot length, shoot diameter, aboveground and root dry weight, internode length, root dry weight/total dry weight, relative growth rate and leaf nitrogen content) was analysed in a replicated block experiment with two water treatments. A composite interval mapping approach was used to estimate number of QTL, the magnitude of the QTL and their position on genetic linkage maps. QTL specific for each treatment and for the treatment index were found, but QTL common across the treatments and the treatment index were also detected. Each QTL explained from 8% to 29% of the phenotypic variation, depending on trait and treatment. Clusters of QTL for different traits were mapped close to each other at several linkage groups, indicating either a common genetic base or tightly linked QTL. Common QTL identified between treatments and treatment index in the complex trait dry weight can be useful tools in the breeding and selection for drought stress tolerance in Salix.     

Fine‐mapping of Obesity‐related Quantitative Trait Loci in an F9/10 Advanced Intercross Line

Obesity develops in response to a combination of environmental effects and multiple genes of small effect. Although there has been significant progress in characterizing genes in many pathways contributing to metabolic disease, knowledge about the relationships of these genes to each other and their joint effects upon obesity lags behind. The LG,SM advanced intercross line (AIL) model of obesity has been used to characterize over 70 loci involved in fatpad weight, body weight, and organ weights. Each of these quantitative trait loci (QTLs) encompasses large regions of the genome and require fine‐mapping to isolate causative sequence changes and possible mechanisms of action as indicated by the genetic architecture. In this study we fine‐map QTLs first identified in the F₂ and F_2/3 populations in the combined F_9/10 advanced intercross generations. We observed significantly narrowed QTL confidence regions, identified many single QTL that resolve into multiple QTL peaks, and identified new QTLs that may have been previously masked due to opposite gene effects at closely linked loci. We also present further characterization of the pleiotropic and epistatic interactions underlying these obesity‐related traits.     

Quantitative genetics of growth and development in Populus. I. A three-generation comparison of tree architecture during the first 2 years of growth

One approach to gain an insight into the genetics of tree architecture is to make use of morphologically divergent parents and study their segregating progeny in the F₂ and backcross (B₁) generations. This approach was chosen in the present study in which material of a three-generation pedigree growing side by side in a replicated plantation, was analyzed. The pedigree included Populus trichocarpa (T) and P. deltoides (D) parents, their F₁ and F₂ hybrids and their B₁ hybrids to the D parent. The trees were grown in the environment of the T parent and measured for the first 2 years of growth. Nine quantitative traits were studied at the stem, branch and leaf levels of tree architecture, in which the original parents differed. Strong F₁ hybrid vigor relative to the better parent (T) was expressed in growth and its components. Most quantitative traits in the F₂ and B₁ hybrids were intermediate between the T and D parents but displayed a wide range of variation due to segregation. The results from the analysis of variance indicated that all morphometric traits were significantly different among F₂ and B₁ clones, but the B₁ hybrids were more sensitive to replicates than the F₂. Broad-sense heritabilities (H ²) based on clonal means ranged from moderately high to high (0.50–0.90) for the traits studied, with H ² values varying over age. The H ² estimates reflected greater environmental noise in the B₁ than in the F₂, presumably due to the greater proportion of maladaptive D alleles in those hybrids. In both families, sylleptic branch number and length, and leaf size on the terminal, showed strong genetic correlations with stem growth. The large divergence between the two original parents in the traits studied, combined with the high chromosome number in Populus (2n=38), makes this pedigree well suited for the estimation of the number of quantitative trait loci (QTLs) underlying quantitative variation by Wright's biometric method (1968). Variation in several traits was found to be under the control of surprisingly few major QTLs: 3–4 in 2nd-year height and diameter growth, a single QTL in stem diameter/height ratio.     

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.     

QTL mapping of resistance to Sclerotinia midstalk rot in RIL of sunflower population NDBLOSsel × CM625

Midstalk rot caused by Sclerotinia sclerotiorum is an important disease of sunflower in its main areas of cultivation. The objectives of this study were to (1) verify quantitative trait loci (QTL) for midstalk-rot resistance found in F₃ families of the NDBLOS_sel × CM625 population in recombinant inbred lines (RIL) derived from the same cross; (2) re-estimate their position and genetic effects; (3) draw inferences about the predictive quality of QTL for midstalk-rot resistance identified in the F₃ families as compared to those in the RIL. Phenotypic data for three resistance (leaf lesion, stem lesion, and speed of fungal growth) and two morphological traits (leaf length and leaf length with petiole) were obtained from 317 RIL following artificial infection in field experiments across two environments. For genotyping the 248 RIL, we selected 41 simple sequence repeat (SSR) markers based on their association with QTL for Sclerotinia midstalk-rot resistance in an earlier study. The resistance traits showed intermediate to high heritabilities and were significantly correlated with each other Genotypic correlations between F₃ families and the RIL were highly significant and ranged between 0.50 for leaf length and 0.64 for stem lesion. For stem lesion, two genomic regions on linkage group (LG) 8 and LG16 explaining 26.5% of the genotypic variance for Sclerotinia midstalk-rot resistance were consistent across generations. For this trait, the genotypic correlation between the observed performance and its prediction based on QTL positions and effects in F₃ families was surprisingly high The genetic effects and predictive quality of these two QTL are promising for application in marker-assisted selection to Sclerotinia midstalk-rot resistance.     

Relationship between heterosis and heterozygosity at marker loci: a theoretical computation

Summary In this paper we have studied the linear correlation between a genetic distance index between two parent lines (based on marker loci information) and the heterosis observed in the F₁ hybrid from the two lines, for a quantitative character (determined by several loci, or QTL). Theoretical computations of the correlation coefficient () between the distance index and the heterosis were made, assuming the biallelic model (defined by Fisher). When the alleles at both marker loci and QTL are equally distributed among the whole population of considered lines, the coefficient is a function of the squares of linkage disequilibria between alleles at marker loci and alleles at QTL. The QTL that are not marked by marker loci and marker loci that do not mark any QTL play symmetrical roles and can decrease greatly. We conclude that the prediction of F₁ hybrid heterosis based on marker loci would be more efficient if these markers were selected for their relationship to the alleles implicated in the heterotic traits considered.     

Epistatic QTL pairs associated with meat quality and carcass composition traits in a porcine Duroc × Pietrain population

Background

Quantitative trait loci (QTL) analyses in pig have revealed numerous individual QTL affecting growth, carcass composition, reproduction and meat quality, indicating a complex genetic architecture. In general, statistical QTL models consider only additive and dominance effects and identification of epistatic effects in livestock is not yet widespread. The aim of this study was to identify and characterize epistatic effects between common and novel QTL regions for carcass composition and meat quality traits in pig.

Methods

Five hundred and eighty five F₂ pigs from a Duroc × Pietrain resource population were genotyped using 131 genetic markers (microsatellites and SNP) spread over the 18 pig autosomes. Phenotypic information for 26 carcass composition and meat quality traits was available for all F₂ animals. Linkage analysis was performed in a two-step procedure using a maximum likelihood approach implemented in the QxPak program.

Results

A number of interacting QTL was observed for different traits, leading to the identification of a variety of networks among chromosomal regions throughout the porcine genome. We distinguished 17 epistatic QTL pairs for carcass composition and 39 for meat quality traits. These interacting QTL pairs explained up to 8% of the phenotypic variance.

Conclusions

Our findings demonstrate the significance of epistasis in pigs. We have revealed evidence for epistatic relationships between different chromosomal regions, confirmed known QTL loci and connected regions reported in other studies. Considering interactions between loci allowed us to identify several novel QTL and trait-specific relationships of loci within and across chromosomes.     

Genome-wide interval mapping using SNPs identifies new QTL for growth,body composition and several physiological variables in an F2 intercross between fat and lean chicken lines

Background

For decades, genetic improvement based on measuring growth and body composition traits has been successfully applied in the production of meat-type chickens. However, this conventional approach is hindered by antagonistic genetic correlations between some traits and the high cost of measuring body composition traits. Marker-assisted selection should overcome these problems by selecting loci that have effects on either one trait only or on more than one trait but with a favorable genetic correlation. In the present study, identification of such loci was done by genotyping an F₂ intercross between fat and lean lines divergently selected for abdominal fatness genotyped with a medium-density genetic map (120 microsatellites and 1302 single nucleotide polymorphisms). Genome scan linkage analyses were performed for growth (body weight at 1, 3, 5, and 7 weeks, and shank length and diameter at 9 weeks), body composition at 9 weeks (abdominal fat weight and percentage, breast muscle weight and percentage, and thigh weight and percentage), and for several physiological measurements at 7 weeks in the fasting state, i.e. body temperature and plasma levels of IGF-I, NEFA and glucose. Interval mapping analyses were performed with the QTLMap software, including single-trait analyses with single and multiple QTL on the same chromosome.

Results

Sixty-seven QTL were detected, most of which had never been described before. Of these 67 QTL, 47 were detected by single-QTL analyses and 20 by multiple-QTL analyses, which underlines the importance of using different statistical models. Close analysis of the genes located in the defined intervals identified several relevant functional candidates, such as ACACA for abdominal fatness, GHSR and GAS1 for breast muscle weight, DCRX and ASPSCR1 for plasma glucose content, and ChEBP for shank diameter.

Conclusions

The medium-density genetic map enabled us to genotype new regions of the chicken genome (including micro-chromosomes) that influenced the traits investigated. With this marker density, confidence intervals were sufficiently small (14 cM on average) to search for candidate genes. Altogether, this new information provides a valuable starting point for the identification of causative genes responsible for important QTL controlling growth, body composition and metabolic traits in the broiler chicken.     

Fine mapping and replication of QTL in outbred chicken advanced intercross lines

Background

Linkage mapping is used to identify genomic regions affecting the expression of complex traits. However, when experimental crosses such as F₂ populations or backcrosses are used to map regions containing a Quantitative Trait Locus (QTL), the size of the regions identified remains quite large, i.e. 10 or more Mb. Thus, other experimental strategies are needed to refine the QTL locations. Advanced Intercross Lines (AIL) are produced by repeated intercrossing of F₂ animals and successive generations, which decrease linkage disequilibrium in a controlled manner. Although this approach is seen as promising, both to replicate QTL analyses and fine-map QTL, only a few AIL datasets, all originating from inbred founders, have been reported in the literature.

Methods

We have produced a nine-generation AIL pedigree (n = 1529) from two outbred chicken lines divergently selected for body weight at eight weeks of age. All animals were weighed at eight weeks of age and genotyped for SNP located in nine genomic regions where significant or suggestive QTL had previously been detected in the F₂ population. In parallel, we have developed a novel strategy to analyse the data that uses both genotype and pedigree information of all AIL individuals to replicate the detection of and fine-map QTL affecting juvenile body weight.

Results

Five of the nine QTL detected with the original F₂ population were confirmed and fine-mapped with the AIL, while for the remaining four, only suggestive evidence of their existence was obtained. All original QTL were confirmed as a single locus, except for one, which split into two linked QTL.

Conclusions

Our results indicate that many of the QTL, which are genome-wide significant or suggestive in the analyses of large intercross populations, are true effects that can be replicated and fine-mapped using AIL. Key factors for success are the use of large populations and powerful statistical tools. Moreover, we believe that the statistical methods we have developed to efficiently study outbred AIL populations will increase the number of organisms for which in-depth complex traits can be analyzed.     

QTL controlling root and shoot traits of maize seedlings under cold stress

The improvement of early vigour is crucial for the adaptation of maize (Zea mays L.) to the climatic conditions of central Europe and the northern Mediterranean, where early sowing is an important strategy for avoiding the effect of summer drought. The objectives of this study were to identify quantitative trait loci (QTL) controlling cold-related traits and to investigate the relationships among them. A set of 168 F_2:4 families of the Lo964 × Lo1016 cross was grown in a sand–vermiculite substrate at 15/13°C (day/night) until the one-leaf stage. Twenty QTL were identified for the four shoot and two seed traits examined. Analysis of root weight and digital measurements of the length and diameter of primary and seminal roots led to the identification of 40 QTL. The operating efficiency of photosystem II (_PSII) was related to seedling dry weight at both the phenotypic and genetic level (r=0.46, two matching loci, respectively) but was not related to root traits. Cluster analysis and QTL association revealed that the different root traits were largely independently inherited and that root lengths and diameters were mostly negatively correlated. The major QTL for root traits detected in an earlier study in hydroponics were confirmed in this study. The length of the primary lateral roots was negatively associated with the germination index (r=–0.38, two matching loci). Therefore, we found a large number of independently inherited loci suitable for the improvement of early seedling growth through better seed vigour and/or a higher rate of photosynthesis.This paper is dedicated to our friend and colleague Alberto Soldati, who passed away unexpectedly.     

Quantitative trait loci for organ weights and adipose fat composition in Jersey and Limousin back‐cross cattle finished on pasture or feedlot

A QTL study of live animal and carcass traits in beef cattle was carried out in New Zealand and Australia. Back‐cross calves (385 heifers and 398 steers) were generated, with Jersey and Limousin backgrounds. This paper reports on weights of eight organs (heart, liver, lungs, kidneys, spleen, gastro‐intestinal tract, fat, and rumen contents) and 12 fat composition traits (fatty acid (FA) percentages, saturated and monounsaturated FA subtotals, and fat melting point). The New Zealand cattle were reared and finished on pasture, whilst Australian cattle were reared on grass and finished on grain for at least 180 days. For organ weights and fat composition traits, 10 and 12 significant QTL locations (P < 0.05), respectively, were detected on a genome‐wide basis, in combined‐sire or within‐sire analyses. Seven QTL significant for organ weights were found at the proximal end of chromosome 2. This chromosome carries a variant myostatin allele (F94L), segregating from the Limousin ancestry, and this is a positional candidate for the QTL. Ten significant QTL for fat composition were found on chromosomes 19 and 26. Fatty acid synthase and stearoyl‐CoA desaturase (SCD1), respectively, are positional candidate genes for these QTL. Two FA QTL found to be common to sire groups in both populations were for percentages of C14:0 and C14:1 (relative to all FAs) on chromosome 26, near the SCD1 candidate gene.