Quantitative trait loci for honey bee stinging behavior and body size.

A study was conducted to identify quantitative trait loci (QTLs) that affect colony-level stinging behavior and individual body size of honey bees. An F1 queen was produced from a cross between a queen of European origin and a drone descended from an African subspecies. Haploid drones from the hybrid queen were individually backcrossed to sister European queens to produce 172 colonies with backcross workers that were evaluated for tendency to sting. Random amplified polymorphic DNA markers were scored from the haploid drone fathers of these colonies. Wings of workers and drones were used as a measure of body size because Africanized bees in the Americas are smaller than European bees. Standard interval mapping and multiple QTL models were used to analyze data. One possible QTL was identified with a significant effect on tendency to sting (LOD 3.57). Four other suggestive QTLs were also observed (about LOD 1.5). Possible QTLs also were identified that affect body size and were unlinked to defensive-behavior QTLs. Two of these were significant (LOD 3.54 and 5.15).     

Genetic determinants of obesity-related lipid traits

In our ongoing effort to identify genes influencing the biological pathways that underlie the metabolic disturbances associated with obesity, we performed genome-wide scanning in 2,209 individuals distributed over 507 Caucasian families to localize quantitative trait loci (QTLs), which affect variation of plasma lipids. Pedigree-based analysis using a quantitative trait variance component linkage method that localized a QTL on chromosome 7q35-q36, which linked to variation in levels of plasma triglyceride [TG, logarithm of odds (LOD) score = 3.7] and was suggestive of linkage to LDL-cholesterol (LDL-C, LOD = 2.2). Covariates of the TG linkage included waist circumference, fasting insulin, and insulin:glucose, but not body mass index or hip circumference. Plasma HDL-cholesterol (HDL-C) levels were suggestively linked to a second QTL on chromosome 12p12.3 (LOD = 2.6). Five other QTLs with lower LOD scores were identified for plasma levels of LDL-C, HDL-C, and total cholesterol. These newly identified loci likely harbor genetic elements that influence traits underlying lipid adversities associated with obesity.     

Segregation and linkage analysis of serum angiotensin I-converting enzyme levels: evidence for two quantitative-trait loci.

Human serum angiotensin I-converting enzyme (ACE) levels vary substantially between individuals and are highly heritable. Segregation analysis in European families has shown that more than half of the total variability in ACE levels is influenced by quantitative-trait loci (QTL). One of these QTLs is located within or close to the ACE locus itself. Combined segregation/linkage analysis in a series of African Caribbean families from Jamaica shows that the ACE insertion-deletion polymorphism is in moderate linkage disequilibrium with an ACE-linked QTL. Linkage analysis with a highly informative polymorphism at the neighboring growth-hormone gene (GH) shows surprisingly little support for linkage (LOD score [Z] = 0.12). An extended analysis with a two-QTL model, where an ACE-linked QTL interacts additively with an unlinked QTL, significantly improves both the fit of the model (P = .002) and the support for linkage between the ACe-linked QTL interacts additively with an unlinked QTL, significantly improves both the fit of the model (P = .002) and the support for linkage between the ACe-linked QTL and GH polymorphism (Z = 5.0). We conclude that two QTLs jointly influence serum ACE levels in this population. One QTL is located within or close to the ACE locus and explains 27% of the total variability; the second QTL is unlinked to the ACE locus and explains 52% of the variability. The identification of the molecular mechanisms underlying both QTLs is necessary in order to interpret the role of ACE in cardiovascular disease.     

Flight and fight: a comparative view of the neurophysiology and genetics of honey bee defensive behavior

Honey bee nest defense involves guard bees that specialize in olfaction-based nestmate recognition and alarm-pheromone-mediated recruitment of nestmates to sting. Stinging is influenced by visual, tactile and olfactory stimuli. Both quantitative trait locus (QTL) mapping and behavioral studies point to guarding behavior as a key factor in colony stinging response. Results of reciprocal F1 crosses show that paternally inherited genes have a greater influence on colony stinging response than maternally inherited genes. The most active alarm pheromone component, isoamyl acetate (IAA) causes increased respiration and may induce stress analgesia in bees. IAA primes worker bees for 'fight or flight', possibly through actions of neuropeptides and/or biogenic amines. Studies of aggression in other species lead to an expectation that octopamine or 5-HT might play a role in honey bee defensive response. Genome sequence and QTL mapping identified 128 candidate genes for three regions known to influence defensive behavior. Comparative bioinformatics suggest possible roles of genes involved in neurogenesis and central nervous system (CNS) activity, and genes involved in sensory tuning through G-protein coupled receptors (GPCRs), such as an arrestin (AmArr4) and the metabotropic GABA(B) receptor (GABA-B-R1).     

Multiple QTLs influence variation in paraoxonase 1 activity in Mexican Americans

Paraoxonase 1 (PON1), a high-density-lipoprotein-associated enzyme known to protect against cellular damage from toxic agents, may also have antioxidant properties. Although the importance of the influence of the PON1 structural locus on chromosome 7q21-22 for variation in the concentration and activity of the enzyme is well-documented, the contribution of other loci is poorly understood. Based on the recent observations of at least one additional quantitative trait locus (QTL) for PON1 activity in pedigreed baboons, we conducted a whole-genome linkage screen for QTLs other than the PON1 structural locus that may influence PON1 activity in humans. We measured PON1 activity in frozen serum for 1,406 individuals in more than 40 extended pedigrees from the San Antonio Family Heart Study (SAFHS). We used a maximum-likelihood-based variance decomposition approach implemented in SOLAR to test for QTLs that may influence PON1 activity. In addition to a QTL for which we detected the strongest, significant evidence (LOD = 31.41) at or near the PON1 structural locus on chromosome 7q21-22, we also localized at least one additional significant QTL on chromosome 12 (LOD = 3.56). Furthermore, we detected suggestive evidence for two more PON-related QTLs on chromosomes 17 and 19. We have provided evidence that other genes, in addition to the well-known ones on chromosome 7, play a role in influencing normal variation in PON1 activity.     

Mapping genetic loci that regulate lipid levels in a NZB/B1NJxRF/J intercross and a combined intercross involving NZB/B1NJ, RF/J, MRL/MpJ, and SJL/J mouse strains

The NZB/B1NJ (NZB) mouse strain exhibits high cholesterol and HDL levels in blood compared with several other strains of mice. To study the genetic regulation of blood lipid levels, we performed a genome-wide linkage analysis in 542 chow-fed F2 female mice from an NZBxRF/J (RF) intercross and in a combined data set that included NZBxRF and MRL/MpJxSJL/J intercrosses. In the NZBxRF F2 mice, the cholesterol and HDL concentrations were influenced by quantitative trait loci (QTL) on chromosome (Chr) 5 [logarithm of odds (LOD) 17-19; D5Mit10] that was in the region identified earlier in crosses involving NZB mice, but two QTLs on Chr 12 (LOD 4.7; D12Mit182) and Chr 19 (LOD 5.7; D19Mit1) were specific to the NZBxRF intercross. Triglyceride levels were affected by two novel QTLs at D12Mit182 (LOD 8.7) and D15Mit13 (LOD 3.5). The combined-cross linkage analysis (1,054 mice, 231 markers) 1) identified four shared QTLs (Chrs 5, 7, 14, and 17) that were not detected in one of the parental crosses and 2) improved the resolution of two shared QTLs. In summary, we report additional loci regulating lipid levels in NZB mice that had not been identified earlier in crosses involving the NZB strain of mice. The identification of shared loci from multiple crosses increases confidence toward finding the QTL gene.     

Identification of diabetes susceptibility loci in db mice by combined quantitative trait loci analysis and haplotype mapping

To identify the disease-susceptibility genes of type 2 diabetes, we performed quantitative trait loci (QTL) analysis in F(2) populations generated from a BKS.Cg-m+/+Lepr(db) and C3H/HeJ intercross, taking advantage of genetically determined obesity and diabetes traits associated with the db gene. A genome-wide scan in the F(2) populations divided by sex and db genotypes identified 14 QTLs in total and 3 major QTLs on chromosome (Chr) 3 (LOD 5.78) for fat pad weight, Chr 15 (LOD 6.64) for body weight, and Chr 16 (LOD 8.15) for blood glucose concentrations. A linear-model-based genome scan using interactive covariates allowed us to consider sex- or sex-by db-specific effects of each locus. For the most significant QTL on Chr 16, the high-resolution haplotype comparison between BKS and C3H strains reduced the critical QTL interval from 20 to 4.6 Mb by excluding shared haplotype regions and identified 11 nonsynonymous single-nucleotide polymorphisms in six candidate genes.     

Quantitative trait loci that regulate plasma lipid concentration in hereditary obese KK and KK-Ay mice

To identify quantitative trait loci (QTLs) responsible for regulating plasma lipid concentration associated with obesity, linkage analysis was carried out on the 190 F2 progeny of a cross between C57BL/6J female and KK-Ay (Ay allele at the agouti locus congenic) male. In F2 a/a (agouti locus genotype) mice, two QTLs were identified on chromosome 1 and a QTL on chromosome 3 for total-cholesterol. A QTL for HDL-cholesterol was identified on chromosome 1 and a QTL for NEFA on chromosome 9. In F2 Ay/a mice, two QTLs for HDL-cholesterol were found on chromosome 1. Loci for other lipids with suggestive linkage were also identified. In both F2 mice, one QTL on chromosome 1 for total- and HDL-cholesterol was mapped near D1Mit150, in the vicinity of the apolipoprotein A-II (Apoa2) locus. Seven nucleotide substitutions out of 309 nucleotide apolipoprotein A-II cDNA sequences were identified between KK and C57BL/6J. The Ay allele may be an indication of the plasma lipid levels, but its influence was less apparent than in the case of weight control. The loci for lipids were not on identical chromosomes with those previously identified for obesity, suggesting that hyperlipidemia in KK does not coincidentally occur with obesity.     

Mapping QTLs for alpha-amylase activity in rye grain

Genetic control of alpha-amylase activity in rye grain was investigated by QTL mapping based on DS2 x RXL10 intercross consisting of 99 F5-6 families propagated at one location during four vegetation seasons. A wide range of variation in alpha-amylase activity and transgression effects were found among families and parental lines. This variation was shown to be determined in 40.1% by 7 significant (LOD score not less than 2.5) and 2 putative QTLs (2 < LOD < 2.5) distributed on all rye chromosomes except 4R. Two significant QTLs located on 3RL and 5RL chromosome arms were expressed each year. The third significant QTL was detected in three years (1RL). The other four significant QTLs (2RL, 5RS, 6RL, 7RL) were found in one year of study. The number and composition of QTLs were specific for a given year varying from three to six. QTLs were not correlated with isoenzyme polymorphisms at the structural alpha-Amy1 loci. A QTL associated with a region containing the alpha-Amy3 locus was detected on chromosome 5RL. Both high- and low-activity QTL alleles were found in each parental line, which explains the appearance of transgressive recombinants in the segregating population.     

Mapping quantitative trait loci associated with leaf and stem pubescence in cotton

Leaf pubescence in cotton have a potential for insect pest management. Varying degrees of leaf trichome density in Gossypium species and cultivars have been associated to a series of five genes, referred to as t(1)-t(5). We used two segregating interspecific G. hirsutum x G. barbadense backcross populations developed in our laboratory to assess qualitatively and quantitatively leaf and stem pubescence. QTL analyses were performed using simple and composite interval mapping. Based on both types of measurements and under both types of QTL analyses, nine QTLs met permutation-based thresholds. The nine QTLs mapped to four different chromosome regions. Highest LOD values corresponded to the QTLs detected on c6 (four colocalized QTLs) and on D03 (two QTLs) for which the higher pubescence in the progeny derived from the pubescent G. hirsutum parent alleles. Conversely, on c17 (one QTL) and A01 (two QTLs), the G. hirsutum parental alleles affected negatively pubescence. These results combined with another published study confirm (1) the location in a center region of chromosome 6 of the t(1) locus as a major locus/gene determining leaf pubescence, and (2) additional genes located on seven additional chromosomes have been shown to impart trichome density either positively or negatively. The existence of a high density of PCR-based loci in most of the regions identified as harboring leaf pubescence QTLs, particularly that on chromosome 6, will facilitate future efforts for map-based cloning.     

Multiple QTLs influencing triglyceride and HDL and total cholesterol levels identified in families with atherogenic dyslipidemia

We conducted a genome-wide scan using variance components linkage analysis to localize quantitative-trait loci (QTLs) influencing triglyceride (TG), high density lipoprotein-cholesterol (HDL-C), low density lipoprotein-cholesterol, and total cholesterol (TC) levels in 3,071 subjects from 459 families with atherogenic dyslipidemia. The most significant evidence for linkage to TG levels was found in a subset of Turkish families at 11q22 [logarithm of the odds ratio (LOD)=3.34] and at 17q12 (LOD=3.44). We performed sequential oligogenic linkage analysis to examine whether multiple QTLs jointly influence TG levels in the Turkish families. These analyses revealed loci at 20q13 that showed strong epistatic effects with 11q22 (conditional LOD=3.15) and at 7q36 that showed strong epistatic effects with 17q12 (conditional LOD=3.21). We also found linkage on the 8p21 region for TG in the entire group of families (LOD=3.08). For HDL-C levels, evidence of linkage was identified on chromosome 15 in the Turkish families (LOD=3.05) and on chromosome 5 in the entire group of families (LOD=2.83). Linkage to QTLs for TC was found at 8p23 in the entire group of families (LOD=4.05) and at 5q13 in a subset of Turkish and Mediterranean families (LOD=3.72). These QTLs provide important clues for the further investigation of genes responsible for these complex lipid phenotypes. These data also indicate that a large proportion of the variance of TG levels in the Turkish population is explained by the interaction of multiple genetic loci.     

Suppression of queen rearing in European and Africanized honey beesApis mellifera L. by synthetic queen mandibular gland pheromone

Summary Queen rearing is suppressed in honey bees (Apis mellifera L.) by pheromones, particularly the queen's mandibular gland pheromone. In this study we compared this pheromonally-based inhibition between temperate and tropically-evolved honey bees. Colonies of European and Africanized bees were exposed to synthetic queen mandibular gland pheromone (QMP) for ten days following removal of resident queens, and their queen rearing responses were examined. Queen rearing was suppressed similarly in both European and Africanized honey bees with the addition of synthetic QMP, indicating that QMP acts on workers of both races in a comparable fashion. QMP completely suppressed queen cell production for two days, but by day six, cells containing queen larvae were present in all treated colonies, indicating that other signals play a role in the suppression of queen rearing. In queenless control colonies not treated with QMP, Africanized bees reared 30% fewer queens than Europeans, possibly due to racial differences in response to feedback from developing queens and/or their cells. Queen development rate was faster in Africanized colonies, or they selected older larvae to initiate cells, as only 1 % of queen cells were unsealed after 10 days compared with 12% unsealed cells in European colonies.     

Honeybee colony drone production and maintenance in accordance with environmental factors: an interplay of queen and worker decisions

Social insect colonies display a remarkable ability to adjust investment in reproduction (i.e., production of sexuals) in accordance with environmental conditions such as season and food availability. How this feat is accomplished by the colony’s queen(s) and workers remains a puzzle. Here, I review what we have learned about this subject in the European honeybee (Apis mellifera), specifically with regard to a colony’s production of males (drones). I identify five environmental conditions that influence colony-level patterns of drone production and then define five stages of drone rearing that are accomplished by the queen and workers. Using this framework, I detail our current understanding of how the queen or workers adjust their actions at each stage of drone rearing in response to each of the environmental conditions. Future investigations of this topic in honeybees and other social insect societies will lead to a better understanding of how colonies manage to flexibly and efficiently allocate their resources under changing environmental conditions.     

Mapping of post-flowering drought resistance traits in grain sorghum: association between QTLs influencing premature senescence and maturity

The identification of genetic factors underlying the complex responses of plants to drought stress provides a solid basis for improving drought resistance. The stay-green character in sorghum (Sorghum bicolor L. Moench) is a post-flowering drought resistance trait, which makes plants resistant to premature senescence under drought stress during the grainfilling stage. The objective of this study was to identify quantitative trait loci (QTLs) that control premature senescence and maturity traits, and to investigate their association under post-flowering drought stress in grain sorghum. A genetic linkage map was developed using a set of recombinant inbred lines (RILs) obtained from the cross B35 × Tx430, which were scored for 142 restriction fragment length polymorphism (RFLP) markers. The RILs and their parental lines were evaluated for post-flowering drought resistance and maturity in four environments. Simple interval mapping identified seven stay-green QTLs and two maturity QTLs. Three major stay-green QTLs (SGA, SGD and SGG) contributed to 42% of the phenotypic variability (LOD 9.0) and four minor QTLs (SGB, SGI.1, SGI.2, and SGJ) significantly contributed to an additional 25% of the phenotypic variability in stay-green ratings. One maturity QTL (DFB) alone contributed to 40% of the phenotypic variability (LOD 10.0), while the second QTL (DFG) significantly contributed to an additional 17% of the phenotypic variability (LOD 4.9). Composite interval mapping confirmed the above results with an additional analysis of the QTL × Environment interaction. With heritability estimates of 0.72 for stay-green and 0.90 for maturity, the identified QTLs explained about 90% and 63% of genetic variability for stay-green and maturity traits, respectively. Although stay-green ratings were significantly correlated (r=0.22, P ≤ 0.05) with maturity, six of the seven stay-green QTLs were independent of the QTLs influencing maturity. Similarly, one maturity QTL (DFB) was independent of the stay-green QTLs. One stay-green QTL (SGG), however, mapped in the vicinity of a maturity QTL (DFG), and all markers in the vicinity of the independent maturity QTL (DFB) were significantly (P ≤ 0.1) correlated with stay-green ratings, confounding the phenotyping of stay-green. The molecular genetic analysis of the QTLs influencing stay-green and maturity, together with the association between these two inversely related traits, provides a basis for further study of the underlying physiological mechanisms and demonstrates the possibility of improving drought resistance in plants by pyramiding the favorable QTLs. Received: 10 October 1998 / Accepted: 12 July 1999     

QTL mapping for genetic determinants of lipoprotein cholesterol levels in combined crosses of inbred mouse strains

To identify additional loci that influence lipoprotein cholesterol levels, we performed quantitative trait locus (QTL) mapping in offspring of PERA/EiJxI/LnJ and PERA/EiJxDBA/2J intercrosses and in a combined data set from both crosses after 8 weeks of consumption of a high fat-diet. Most QTLs identified were concordant with homologous chromosomal regions that were associated with lipoprotein levels in human studies. We detected significant new loci for HDL cholesterol levels on chromosome (Chr) 5 (Hdlq34) and for non-HDL cholesterol levels on Chrs 15 (Nhdlq9) and 16 (Nhdlq10). In addition, the analysis of combined data sets identified a QTL for HDL cholesterol on Chr 17 that was shared between both crosses; lower HDL cholesterol levels were conferred by strain PERA. This QTL colocalized with a shared QTL for cholesterol gallstone formation detected in the same crosses. Haplotype analysis narrowed this QTL, and sequencing of the candidate genes Abcg5 and Abcg8 confirmed shared alleles in strains I/LnJ and DBA/2J that differed from the alleles in strain PERA/EiJ. In conclusion, our analysis furthers the knowledge of genetic determinants of lipoprotein cholesterol levels in inbred mice and substantiates the hypothesis that polymorphisms of Abcg5/Abcg8 contribute to individual variation in both plasma HDL cholesterol levels and susceptibility to cholesterol gallstone formation.     

The honeybee queen influences the regulation of colony drone production

Social insect colonies invest in reproduction and growth, buthow colonies achieve an adaptive allocation to these life-historycharacters remains an open question in social insect biology.Attempts to understand how a colony's investment in reproductionis shaped by the queen and the workers have proved complicatedbecause of the potential for queen–worker conflict overthe colony's investment in males versus females. Honeybees,in which this conflict is expected to be minimal or absent,provide an opportunity to more clearly study how the actionsand interactions of individuals influence the colony's productionand regulation of males (drones). We examined whether honeybeequeens can influence drone regulation by either allowing orpreventing them from laying drone eggs for a period of timeand then examining their subsequent tendency to lay drone andworker eggs. Queens who initially laid drone eggs subsequentlylaid fewer drone eggs than the queens who were initially preventedfrom producing drone eggs. This indicates that a colony's regulationof drones may be achieved not only by the workers, who buildwax cells for drones and feed the larvae, but also by the queen,who can modify her production of drone eggs. In order to betterunderstand how the queen and workers contribute to social insectcolony decisions, future work should attempt to distinguishbetween actions that reflect conflict over sex allocation andthose that reflect cooperation and shared control over the colony'sinvestment in reproduction.     

Three QTL in the honey bee Apis mellifera L. suppress reproduction of the parasitic mite Varroa destructor

Varroa destructor is a highly virulent ectoparasitic mite of the honey bee Apis mellifera and a major cause of colony losses for global apiculture. Typically, chemical treatment is essential to control the parasite population in the honey bee colony. Nevertheless a few honey bee populations survive mite infestation without any treatment. We used one such Varroa mite tolerant honey bee lineage from the island of Gotland, Sweden, to identify quantitative trait loci (QTL) controlling reduced mite reproduction. We crossed a queen from this tolerant population with drones from susceptible colonies to rear hybrid queens. Two hybrid queens were used to produce a mapping population of haploid drones. We discriminated drone pupae with and without mite reproduction, and screened the genome for potential QTL using a total of 216 heterozygous microsatellite markers in a bulk segregant analysis. Subsequently, we fine mapped three candidate target regions on chromosomes 4, 7, and 9. Although the individual effect of these three QTL was found to be relatively small, the set of all three had significant impact on suppression of V. destructor reproduction by epistasis. Although it is in principle possible to use these loci for marker-assisted selection, the strong epistatic effects between the three loci complicate selective breeding programs with the Gotland Varroa tolerant honey bee stock.     

Pooled analysis of data from multiple quantitative trait locus mapping populations

Quantitative trait locus (QTL) analysis on pooled data from multiple populations (pooled analysis) provides a means for evaluating, as a whole, evidence for existence of a QTL from different studies and examining differences in gene effect of a QTL among different populations. Objectives of this study were to: (1) develop a method for pooled analysis and (2) conduct pooled analysis on data from two soybean mapping populations. Least square interval mapping was extended for pooled analysis by inclusion of populations and cofactor markers as indicator variables and covariate variables separately in the multiple linear models. The general linear test approach was applied for detecting a QTL. Single population-based and pooled analyses were conducted on data from two F_2:3 mapping populations, Hamilton (susceptible) × PI 90763 (resistant) and Magellan (susceptible) × PI 404198A (resistant), for resistance to soybean cyst nematode (SCN) in soybean. It was demonstrated that where a QTL was shared among populations, pooled analysis showed increased LOD values on the QTL candidate region over single population analyses. Where a QTL was not shared among populations, however, the pooled analysis showed decreased LOD values on the QTL candidate region over single population analyses. Pooled analysis on data from genetically similar populations may have higher power of QTL detection than single population-based analyses. QTLs were identified by pooled analysis on linkage groups (LGs) G, B1 and J for resistance to SCN race 2 whereas QTLs on LGs G, B1 and E for resistance to SCN race 5 in soybean PI 90763 and PI 404198A. QTLs on LG G and B1 were identified in both PI 90763 and PI 404198A whereas QTLs on LG E and J were identified in PI 90763 only. QTLs on LGs G and B1 for resistance to race 2 may be the same or closely linked with QTLs on LG G and B1 for resistance to race 5, respectively. It was further demonstrated that QTLs on G and B1 carried by PI 90763 were not significantly different in gene effect from QTLs on LGs G and B1 in PI 404198A, respectively.     

Epistasis between QTLs for bone density variation in Copenhagen × dark agouti F2 rats

The variation in several of the risk factors for osteoporotic fracture, including bone mineral density (BMD), has been shown to be strongly influenced by genetic differences. However, the genetic architecture of BMD is complex in both humans and in model organisms. We previously reported quantitative trait locus (QTL) results for BMD from a genome screen of 828 F2 progeny of Copenhagen and dark agouti rats. These progeny also provide an excellent opportunity to search for epistatic effects, or interaction between genetic loci, that contribute to fracture risk. Microsatellite marker data from a 20-cM genome screen was analyzed along with weight-adjusted bone density (DXA and pQCT) phenotypic data using the R/qtl software package. Genotype and phenotype data were permuted to determine genome-wide significance thresholds for the full model and epistasis (interaction) LOD scores corresponding to an alpha level of 0.01. A novel locus on chromosome 15 and a previously reported chromosome 14 QTL demonstrated a strong epistatic effect on BMD at the femur by DXA (LOD = 5.4). Two novel QTLs on chromosomes 2 and 12 were found to interact to affect total BMD at the femur midshaft by pQCT (LOD = 5.0). These results provide new information regarding the mode of action of previously identified QTL in the rat, as well as identifying novel loci that act in combination with known QTL or with other novel loci to contribute to BMD variation.