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At least 1,207 records · Page 67Linked to original sources
PubMed2003

Identification of genetically linked RGAs by BAC screening in maize and implications for gene cloning, mapping and MAS.

The resistance gene analogue (RGA) pic19 in maize, a candidate for sugarcane mosaic virus (SCMV) resistance gene (R gene) Scmv1, was used to screen a maize BAC library to identify homologous sequences in the maize genome and to investigate their genomic organisation. Fifteen positive BAC clones were identified and could be classified into five physically independent contigs consisting of overlapping clones. Genetic mapping clustered three contigs into the same genomic region as Scmv1 on chromosome 6S. The two remaining contigs mapped to the same region as a QTL for SCMV resistance on chromosome 1. Thus, RGAs mapping to a target region can be successfully used to identify further-linked candidate sequences. The pic19 homologous sequences of these clones revealed a sequence similarity of 94-98% on the nucleotide level. The high sequence similarity reveals potential problems for the use of RGAs as molecular markers. Their application in marker-assisted selection (MAS) and the construction of high-density genetic maps is complicated by the existence of closely linked homologues resulting in 'ghost' marker loci analogous to 'ghost' QTLs. Therefore, implementation of genomic library screening, including genetic mapping of potential homologues, seems necessary for the safe application of RGA markers in MAS and gene isolation.

Base Sequence↗
PubMed2003

Localization of QTLs for yield and fiber quality traits of tetraploid cotton cultivar.

Using SSR and RAPD as molecular markers, and the 69 F2 families from a cross between Handan208 (Gossypium hirsutum) and Pima90 (Gossypium barbadense) as a mapping population, a linkage map comprising 126 markers was constructed. With an average spacing 13.7 cM between markers, the linkage map spanned 1,717.0 cM, which covers approximately 34.34% of the total recombinational length of cotton genome. Based on the linkage map and the F2:3 phenotypic data, overall genome QTL screening was conducted by composite interval mapping method, then 29 QTLs related to cotton yield traits and fiber quality traits were found. There are 16 loci related to yield traits and 13 loci related to fiber quality. Particularly, two QTLs relevant to fiber strength were detected, which could explain phenotypic variance of 34.15% and 13.86%, respectively.

Genetic Linkage↗
PubMed1996

Genetic interactions between naturally occurring alleles at quantitative trait loci and mutant alleles at candidate loci affecting bristle number in Drosophila melanogaster.

Previously, we mapped quantitative trait loci (QTL) affecting response to short-term selection for abdominal bristle number to seven suggestive regions that contain loci involved in bristle development and/or that have adult bristle number mutant phenotypes, and are thus candidates for bristle number QTL in natural populations. To test the hypothesis that the factors contributing to selection response genetically interact with these candidate loci, high and low chromosomes from selection lines were crossed to chromosomes containing wild-type or mutant alleles at the candidate loci, and the numbers of bristles were recorded in trans heterozygotes. Quantitative failure to complement, detected as a significant selection line*cross effect by analysis of variance, can be interpreted as evidence for allelism or epistasis between the factors on selected chromosomes and the candidate loci. Mutations at some candidate loci (bb, emc, h, Dl, Hairless) showed strong interactions with selected chromosomes, whereas others interacted weakly (ASC, abd, Scr) or not at all (N, mab, E(spl)). These results support the hypothesis that some candidate loci, initially identified through mutations of large effect on bristle number, either harbor or are close members in the same genetic pathway as variants that contribute to standing variation in bristle number.

Alleles↗
PubMed2026

Multi-omics analysis identifies key genes and functional loci affecting teat number in American Large White and Landrace pigs and their application in optimizing genomic selection models.

BACKGROUND: Teat number is a crucial economic trait in pigs. It directly affects the ability of sows to lactate, which in turn influences the survival and health of piglets. The teat number of French Large White pigs is close to 16, while the teat number of American Large White and Landrace pigs is about 14. In order to improve the teat number of American Landrace and Large White pigs through molecular approaches and precise breeding techniques, we genotyped 2,131 American Landrace and 4,564 American Large White with teat number phenotype using a 50 K SNP chip. Then, the SNP-chip data was imputed to the level of whole-genome sequencing (iWGS). Based on iWGS data, we conducted GWAS to identify novel, significant SNPs associated with teat number and to incorporate them into genomic selection. RESULTS: In Landrace pigs, significant SNPs for TTN mapped to SSC2, SSC7, SSC8, and SSC14; the SSC8 and SSC14 effects are novel. LTN mapped to SSC7, RTN to SSC7 and SSC8. The lead SSC7 SNP explained 2.60% of TTN phenotypic variance. In Large White pigs, significant SNPs were detected on SSC7 and SSC10 for TTN; SSC7, SSC10, and SSC12 for LTN; and SSC7 and SSC10 for RTN. The most significant locus on SSC7 accounted for 2.99% of the phenotypic variance in TTN. Additionally, a multi-population meta-analysis detected significant novel SNPs for LTN on SSC1 and SSC8. By utilizing Bayesian fine mapping, the most precise QTL confidence interval on SSC7 for both TTN and RTN in Large White pigs was reduced to 40 kb. By integrating functional gene annotation with RNA-seq and ATAC-seq data from Erhualian and Bamaxiang pigs mammary placodes at embryonic day 26, we prioritized PTPN13, TRPV3, ZDHHC13, and BRD2 as novel candidate genes for teat number. We then incorporated the significant SNPs to GBLUP and benchmarked genomic-selection accuracy. In both breeds, fitting the top SNP as fixed maximized prediction for TTN and RTN, whereas treating all significant loci as an additional random effect optimized LTN. CONCLUSIONS: Our findings provide a theoretical basis for dissecting new key genes affecting teat number and for advancing molecular breeding of teat number in pigs.

Animals↗
PubMed2006

Detection of a quantitative trait locus for both foliage and tuber resistance to late blight [Phytophthora infestans (Mont.) de Bary] on chromosome 4 of a dihaploid potato clone (Solanum tuberosum subsp. tuberosum).

Linkage analysis, Kruskal-Wallis analysis, interval mapping and graphical genotyping were performed on a potato diploid backcross family comprising 120 clones segregating for resistance to late blight. A hybrid between the Solanum tuberosum dihaploid clone PDH247 and the long-day-adapted S. phureja clone DB226(70) had been crossed to DB226(70) to produce the backcross family. Eighteen AFLP primer combinations provided 186 and 123 informative maternal and paternal markers respectively, with 63 markers in common to both parents. Eleven microsatellite (SSR) markers proved useful for identifying chromosomes. Linkage maps of both backcross parents were constructed. The results of a Kruskal-Wallis analysis, interval mapping and graphical genotyping were all consistent with a QTL or QTLs for blight resistance between two AFLP markers 30 cM apart on chromosome 4, which was identified by a microsatellite marker. The simplest explanation of the results is a single QTL with an allele from the dihaploid parent conferring resistance to race 1, 4 of P. infestans in the foliage in the glasshouse and to race 1, 2, 3, 4, 6, 7 in the foliage in the field and in tubers from glasshouse raised plants. The QTL was of large effect, and explained 78 and 51% of the variation in phenotypic scores for foliage blight in the glasshouse and field respectively, as well as 27% of the variation in tuber blight. Graphical genotyping and the differences in blight scores between the parental clones showed that all of the foliage blight resistance is accounted for by chromosome 4, whereas undetected QTLs for tuber resistance probably exist on other chromosomes. Graphical genotyping also explained the lack of precision in mapping the QTL(s) in terms of lack of appropriate recombinant chromosomes.

Chromosome Mapping↗
PubMed2004

Potential pleiotropic effects of Mpdz on vulnerability to seizures.

We previously mapped quantitative trait loci (QTL) responsible for approximately 26% of the genetic variance in acute alcohol and barbiturate (i.e., pentobarbital) withdrawal convulsion liability to a < 1 cM (1.8 Mb) interval of mouse chromosome 4. To date, Mpdz, which encodes the multiple PSD95/DLG/ZO-1 (PDZ) domain protein (MPDZ), is the only gene within the interval shown to have allelic variants that differ in coding sequence and/or expression, making it a strong candidate gene for the QTL. Previous work indicates that Mpdz haplotypes in standard mouse strains encode distinct protein variants (MPDZ1-3), and that MPDZ status is genetically correlated with severity of withdrawal from alcohol and pentobarbital. Here, we report that MPDZ status cosegregates with withdrawal convulsion severity in lines of mice selectively bred for phenotypic differences in severity of acute withdrawal from alcohol [i.e., High Alcohol Withdrawal (HAW) and Low Alcohol Withdrawal (LAW) lines] or pentobarbital [High Pentobarbital Withdrawal (HPW) and Low Pentobarbital Withdrawal (LPW) lines]. These analyses confirm that MPDZ status is associated with severity of alcohol and pentobarbital withdrawal convulsions. Using a panel of standard inbred strains of mice, we assessed the association between MPDZ status with seizures induced by nine chemiconvulsants. Our results show that MPDZ status is genetically correlated with seizure sensitivity to pentylenetetrazol, kainate and other chemiconvulsants. Our results provide evidence that Mpdz may have pleiotropic effects on multiple seizure phenotypes, including seizures associated with withdrawal from two classes of central nervous system (CNS) depressants and sensitivity to specific chemiconvulsants that affect glutaminergic and GABAergic neurotransmission.

Amino Acid Motifs↗
PubMed2001

Genetic architecture of testis and seminal vesicle weights in mice.

Comparisons across 13 inbred strains of laboratory mice for reproductive organ (paired seminal vesicles and paired testes) weights indicated a very marked contrast between the C57BL/6By and NZB/BINJ mice. Subsequently these strains were selected to perform a quantitative genetic analysis and full genome scan for seminal vesicle and testis weights. An F(2) population was generated. The quantitative genetic analyses indicated that each was linked to several genes. Sixty-six short sequences for length polymorphism were used as markers in the wide genome scan strategy. For weight of paired testes, heritability was 82.3% of the total variance and five QTL contributed to 72.8% of the total variance. Three reached a highly significant threshold (>4.5) and were mapped on chromosome X (LOD score 9.11), chromosome 4 (LOD score 5.96), chromosome 10 (LOD score 5.81); two QTL were suggested: chromosome 13 (LOD score 3.10) and chromosome 18 (LOD score 2.80). Heritability for weight of seminal vesicles was 50.7%. One QTL was mapped on chromosome 4 (LOD score 9.21) and contributed to 24.2% of the total variance. The distance of this QTL to the centromere encompassed the distance of the QTL linked with testicular weight on chromosome 4, suggesting common genetic mechanisms as expected from correlations in the F(2). Both testis and seminal vesicle weights were associated with a reduction in the NZB/BINJ when this strain carried the Y(NPAR) from CBA/H whereas the Y(NPAR) from NZB/BINJ in the CBA/H strain did not modify reproductive organ weights, indicating that the Y(NPAR) interacts with the non-Y(NPAR) genes. The effects generated by this chromosomal region were significant but small in size.

Animals↗
PubMed2005

Mapping of barley homologs to genes that regulate low temperature tolerance in Arabidopsis.

We investigated the allelic nature and map locations of Hordeum vulgare (barley) homologs to three classes of Arabidopsis low temperature (LT) regulatory genes-CBFs, ICE1, and ZAT12-to determine if there were any candidates for winterhardiness-related quantitative trait loci (QTL). We phenotyped the Dicktoo x Morex (DxM) mapping population under controlled freezing conditions and in addition to the previously reported 5H-L Fr-H1 QTL, observed three additional LT tolerance QTLs on 1H-L, 4H-S, and 4H-L. We identified and assigned either linkage map or chromosome locations to 1 ICE1 homolog, 2 ZAT12 homologs, and 17 of 20 CBF homologs. Twelve of the CBF genes were located on 5H-L and the 11 with assigned linkage map positions formed 2 tandem clusters on 5H-L. A subset of these CBF genes was confirmed to be physically linked, validating the map position clustering. The tandem CBF clusters are not candidates for the DxM LT tolerance Fr-H1 QTL, as they are approximately 30 cM distal to the QTL peak. No LT tolerance QTL was detected in conjunction with the CBF gene clusters in Dicktoo x Morex. However, comparative mapping using common markers and BIN positions established the CBF clusters are coincident with reported Triticeae LT tolerance and COR gene accumulation QTLs and suggest one or more of the CBF genes may be candidates for Fr-H2 in some germplasm combinations. These results suggest members of the CBF gene family may function as components of winter-hardiness in the Triticeae and underscore both the importance of extending results from model systems to economically important crop species and in viewing QTL mapping results in the context of multiple germplasm combinations.

Alleles↗
PubMed2004

A large-sample QTL study in mice: II. Body composition.

Using lines of mice having undergone long-term selection for high and low growth, a large-sample (n = approximately 1,000 F2) experiment was conducted to gain further understanding of the genetic architecture of complex polygenic traits. Composite interval mapping on data from male F2 mice (n = 552) detected 50 QTL on 15 chromosomes impacting weights of various organ and adipose subcomponents of growth, including heart, liver, kidney, spleen, testis, and subcutaneous and epididymal fat depots. Nearly all aggregate growth QTL could be interpreted in terms of the organ and fat subcomponents measured. More than 25% of QTL detected map to MMU2, accentuating the relevance of this chromosome to growth and fatness in the context of this cross. Regions of MMU7, 15, and 17 also emerged as important obesity "hot-spots." Average degrees of directional dominance are close to additivity, matching expectations for body composition traits. A strong QTL congruency is evident among heart, liver, kidney, and spleen weights. Liver and testis are organs whose genetic architectures are, respectively, most and least aligned with that for aggregate body weight. In this study, growth and body weight are interpreted in terms of organ subcomponents underlying the macro aggregate traits, and anchored on the corresponding genomic locations.

Animals↗
PubMed2006

QTL with pleiotropic effects on serum levels of bone-specific alkaline phosphatase and osteocalcin maps to the baboon ortholog of human chromosome 6p23-21.3.

UNLABELLED: Bone ALP and OC are under partial genetic control. This study of 591 pedigreed baboons shows a QTL corresponding to human 6p23-21.3 that accounts for 25% (bone ALP) and 20% (OC) of the genetic variance. A gene affecting osteoblast activity, number, or recruitment likely resides in this area. INTRODUCTION: Serum levels of bone alkaline phosphatase (ALP) and osteocalcin (OC) reflect osteoblast activity. Both of these measures are under partial genetic control. Genetic effects on bone ALP have not been previously localized to chromosomal regions in primates, nor has the degree to which genetic effects are shared (pleiotropic) between bone ALP and OC been studied. MATERIALS AND METHODS: We applied variance components methods to a sample of 591 adult pedigreed baboons to detect and quantify effects of genes that influence bone ALP and that have pleiotropic effects on bone ALP and OC. A univariate linkage analysis was conducted for bone ALP. Bivariate linkage analyses were conducted in areas for which the bone ALP results presented here and a previous univariate OC linkage analysis showed evidence for linkage on the same chromosome for both bone ALP and OC. RESULTS: A quantitative trait locus (QTL) for serum levels of bone ALP is evident on the baboon ortholog of human chromosomal region 6p (LOD 2.93). Thirty-seven percent (genetic correlation [rho(G)] = 0.61) of the genetic variance in bone ALP and OC is caused by pleiotropic effects of the same gene(s). Bivariate linkage analysis revealed a QTL in the region corresponding to human chromosome 6p23-21.3, with the strongest evidence for bivariate linkage near D6S422 (LOD = 2.97 at 22 cM from our pter-most marker). D6S422 maps to 20.4 Mb in the human genome. The QTL-specific heritability (h2) is 0.25 and 0.20 for bone ALP and OC, respectively. CONCLUSIONS: This first formal test for shared genetic effects on two serum markers of osteoblast activity indicates that a significant pleiotropic effect on bone ALP and OC levels, and thus on bone formation, is detectible. The fact that this region corresponds to one on mouse chromosome 13 that has repeatedly yielded QTLs for BMD should encourage more intensive study of the effect of genes in this region on bone maintenance and turnover.

Alkaline Phosphatase↗
PubMed2006

Mapping quantitative trait loci associated with selenate tolerance in Arabidopsis thaliana.

Selenium is essential for many organisms, but is toxic at higher levels. To investigate the genetic basis of selenate tolerance in Arabidopsis thaliana, quantitative trait loci (QTL) associated with selenate tolerance in accessions Landsberg erecta and Columbia were mapped using recombinant inbred lines (RILs). The selenate tolerance index (TI(D10) = root growth + 30 microm selenate/root growth control x 100%) was fourfold higher for parental line Col-4 (59%) than for parent Ler-0 (15%). Among the 96 F8 RILs, TI(D10) ranged from 11 to 75% (mean 37%). Using composite interval mapping, three QTL were found on chromosomes 1, 3 and 5, which together explained 24% of variation in TI(D10) and 32% of the phenotypic variation for the difference in root length +/- Se (RL(D10)). Highly significant epistatic interactions between the QTL and markers on chromosome 2 explained additional variation for both traits. Potential candidate genes for Se tolerance in each of the QTL regions are discussed. These results offer insight into the genetic basis of selenate tolerance, and may be useful for identification of selenate-tolerance genes.

Arabidopsis↗
PubMed2004

Quantitative trait loci in Chromosomes 3, 8, and 9 regulate antibody production against Salmonella flagellar antigens in the mouse.

Two mouse lines were produced by bidirectional selection according to the high (HIII) or low (LIII) antibody responsiveness against Salmonella flagellar antigens (Selection III). In the present work we conducted a genomewide scan to map the quantitative trait loci (QTL) involved in the antibody response regulation in these selected mice. HIII and LIII genomes were screened with microsatellite markers and those found polymorphic between the lines (146) were used for linkage analysis in F2 (HIII x LIII) intercross. Simple interval mapping analysis was performed using Mapmanager QTX software. Three highly significant QTL linked to antibody production against Salmonella flagellar antigens have been demonstrated in Chromosomes 3, 8, and 9. HIII and LIII lines differ in the resistance to several diseases, therefore, the relevance of these QTL with the genetic factors involved in infections, autoimmunity, and neoplastic disease progression is discussed.

Animals↗
PubMed2005

New Arabidopsis recombinant inbred line populations genotyped using SNPWave and their use for mapping flowering-time quantitative trait loci.

The SNPWave marker system, based on SNPs between the reference accessions Colombia-0 and Landsberg erecta (Ler), was used to distinguish a set of 92 Arabidopsis accessions from various parts of the world. In addition, we used these markers to genotype three new recombinant inbred line populations for Arabidopsis, having Ler as a common parent that was crossed with the accessions Antwerp-1, Kashmir-2, and Kondara. The benefit of using multiple populations that contain many similar markers and the fact that all markers are linked to the physical map of Arabidopsis facilitates the quantitative comparison of maps. Flowering-time variation was analyzed in the three recombinant inbred line populations. Per population, four to eight quantitative trait loci (QTL) were detected. The comparison of the QTL positions related to the physical map allowed the estimate of 12 different QTL segregating for flowering time for which Ler has an allele different from one, two, or three of the other accessions.

Arabidopsis↗
PubMed2000

Quantitative trait loci for root-penetration ability and root thickness in rice: comparison of genetic backgrounds.

Drought is the major abiotic stress limiting rice (Oryza sativa) production and yield stability in rainfed lowland and upland ecosystems. Root systems play an important role in drought resistance. Incorporation of root selection criteria in drought resistance improvement is difficult due to lack of reliable and efficient screening techniques. Using a wax-petrolatum layer system simulated to compacted soil layers, root traits were evaluated in a doubled haploid (DH) population derived from the cross between 'IR64' and 'Azucena'. Twelve putative QTLs (quantitative trait loci) were detected by interval mapping comprising four QTLs for root-penetration ability, four QTLs for root thickness, two QTLs for penetrated root number, and two QTLs for total root number. These QTLs individually explained 8.4% to 16.4% of the phenotypic variation. No QTL was detected for maximum penetrated root length by interval mapping. One QTL located between RG104 and RG348 was found to influence both root-penetration ability and root thickness. QTLs for root-penetration ability and root thickness were compared across two populations, 'IR64'-'Azucena' and 'CO39'-'Moroberekan', and different testing conditions. The identified consistent QTLs could be used for marker-assisted selection for deep and thick roots with high root-penetration ability in rice.

Oryza↗
PubMed2002

Gene-expression profile of collagen-induced arthritis.

To provide a global analysis of genes involved in the inflammatory process in joints of DBA/1J mice suffering from collagen induced arthritis (CIA) we used oligonucleotide microarrays representing approximately 11,000 genes to determine the gene expression profile of the inflamed paws at peak of disease, and compared them to normal tissue. Peak of disease was determined from clinical evaluation of disease and histopathology of joints. Of the 11,000 genes assayed, 223 showed differential expression of four fold or more (187 upregulated and 36 downregulated). Ninety-five of the genes observed had well-characterized full length sequences in databases, and 128 were unknown (Ests). Inflammation resulted in a profile of increased gene expression of matrix metalloproteinases, immune-related, extra-cellular matrix and cell adhesion molecules, as well as molecules involved in cell division and transcription; differential regulation of molecules involved in signal transduction, protein synthesis and metabolism. Of the 55 genes with known chromosomal locations nine mapped to previously identified QTL, contributing to susceptibility or severity of CIA, i.e. MHC class I, II, Basigin, FAP, Cathepsin K, CD 53, RAF1, glucagon, and retinal taurine transporter. The profile of gene expression supports current theoretical models of disease progression and might open new perspectives for both diagnosis and treatment of arthritis.

Animals↗
PubMed1999

A genome-wide search strategy for identifying quantitative trait loci involved in reading and spelling disability (developmental dyslexia).

Family and twin studies of developmental dyslexia have consistently shown that there is a significant heritable component for this disorder. However, any genetic basis for the trait is likely to be complex, involving reduced penetrance, phenocopy, heterogeneity and oligogenic inheritance. This complexity results in reduced power for traditional parametric linkage analysis, where specification of the correct genetic model is important. One strategy is to focus on large multigenerational pedigrees with severe phenotypes and/or apparent simple Mendelian inheritance, as has been successfully demonstrated for speech and language impairment. This approach is limited by the scarcity of such families. An alternative which has recently become feasible due to the development of high-throughput genotyping techniques is the analysis of large numbers of sib-pairs using allele-sharing methodology. This paper outlines our strategy for conducting a systematic genome-wide search for genes involved in dyslexia in a large number of affected sib-pair familites from the UK. We use a series of psychometric tests to obtain different quantitative measures of reading deficit, which should correlate with different components of the dyslexia phenotype, such as phonological awareness and orthographic coding ability. This enable us to use QTL (quantitative trait locus) mapping as a powerful tool for localising genes which may contribute to reading and spelling disability.

Alleles↗
PubMed2001

Identification of quantitative trait loci controlling activation of TRBV4 CD8+ T cells during murine gamma-herpesvirus-induced infectious mononucleosis.

The murine gamma-herpesvirus, MHV-68, shares important biological and genetic features with the human gamma-herpesvirus, Epstein-Barr virus. Following intranasal infection, mice develop an infectious mononucleosis-like syndrome accompanied by increased numbers of activated CD8+ T cells in the blood. A consistent feature of the CD8+ T-cell activation is a marked increase in the frequency of cells expressing a TRBV4+ T-cell receptor. Previous studies suggested that the magnitude of TRBV4 expansion varied significantly among mouse strains, and was influenced by both MHC and non-MHC genes. Detailed analysis of strains with high (C57BL/6) or low (DBA/2) TRBV4 CD8+ T-cell expansion showed that differences in the degree of expansion were not a consequence of variation in genetic susceptibility to the viral infection. Rather, the magnitude of the TRBV4 CD8+ T-cell expansion correlated with differences in expression of the unidentified stimulatory ligand on activated, latently infected B cells. In the present study, analysis of TRBV4 expansion in C57BL/6, DBA/2, B6D2 F1 mice, BXD recombinant inbred strains, and the progeny of C57BL/6xDBA/2 F1 hybrids backcrossed to C57BL/6 demonstrated strong cumulative dominance of the low DBA/2 trait and moderately high heritability (h2 approximately 0.5). Two quantitative trait loci (QTLs) strongly associated with variance in TRBV4 expansion were identified using simple and composite mapping procedures. The first QTL is located on Chromosome (Chr) 17, near or proximal to H2. The second QTL is located on Chr 6 in a region spanning the Tcrb and Cd8a loci.

Animals↗
PubMed2005

Mapping quantitative trait loci using linkage disequilibrium: marker- versus trait-based methods.

Two approaches for mapping quantitative trait loci (QTL) using linkage disequilibrium at the population level were investigated. In the trait-based (TB) approach, the frequencies of marker alleles (or genotypes) are compared in individuals selected from the two tails of the trait distribution. The TB approach uses phenotypic information only in the selection step. In the marker-based (MB) approach, the quantitative trait values for the marker genotypes in the selected individuals are compared. The MB approach uses both the difference in marker allele (or genotype) frequencies and the phenotypic values of each marker genotype in the selected samples. We quantify the power of each approach and show that the power of the MB approach is greater than or equal to that of the TB approach. The advantage of the former is expected to increase with increasing number of traits phenotyped. Our accurate predictions obviate the need for elaborate simulation studies.

Humans↗