Determination of quantitative trait nucleotides by concordance analysis between quantitative trait loci and marker genotypes of US Holsteins.

Experimental designs that exploit family information can provide substantial predictive power in quantitative trait nucleotide discovery projects. Concordance between quantitative trait locus genotype as determined by the a posteriori granddaughter design and marker genotype was determined for 30 trait-by-chromosomal segment effects segregating in the US Holstein population with probabilities of <10-20 to accept the null hypotheses of no segregating gene affecting the trait within the chromosomal segment. Genotypes for 83 grandsires and 17,217 sons were determined by either complete sequence or imputation for 3,148,506 polymorphisms across the entire genome; 471 Holstein bulls had a complete genome sequence, including 64 of the grandsires. Complete concordance was obtained only for stature on chromosome 14 and daughter pregnancy rate on chromosome 18. For each quantitative trait locus, effects of the 30 polymorphisms with highest concordance scores for the analyzed trait were computed by stepwise regression for predicted transmitting abilities of 26,750 bulls with progeny test and imputed genotypes. Effects for stature on chromosome 11, daughter pregnancy rate on chromosome 18, and protein percentage on chromosome 20 met 3 criteria: complete or almost complete concordance, nominal significance of the polymorphism effect after correction for all other polymorphisms, and marker coefficient of determination >40% of total multiple-regression coefficient of determination for the 30 polymorphisms with highest concordance. An intronic variant marker on chromosome 5 at 93,945,738 bp explained 7% of variance for fat percentage and 74% of total multiple-marker regression variance but was concordant for only 24 of 30 families. The missense polymorphism Phe279Tyr in GHR at 31,909,478 bp on chromosome 20 was confirmed as the causative mutation for fat and protein concentration. For effect on fat percentage on chromosome 14, 12 additional missense polymorphisms were found that had almost complete concordance with the suggested causative polymorphism (missense mutation Ala232Glu in DGAT1). The only polymorphism found likely to improve predictive power for genomic evaluation of dairy cattle was on chromosome 15; that polymorphism had a frequency of 0.45 for the allele with economically positive effects on all production traits.

[1]  J. Weller,et al.  A new approach to the problem of multiple comparisons in the genetic dissection of complex traits. , 1998, Genetics.

[2]  J. Weller,et al.  Short communication: a polymorphism in ABCG2 in Bos indicus and Bos taurus cattle breeds. , 2006, Journal of dairy science.

[3]  H. Lewin,et al.  Multisite haplotype on cattle chromosome 3 is associated with quantitative trait locus effects on lactation traits. , 2011, Physiological genomics.

[4]  Jeffrey R. O’Connell,et al.  Selecting sequence variants to improve genomic predictions for dairy cattle , 2017, Genetics Selection Evolution.

[5]  O. Bininda-Emonds,et al.  Evidence for Multiple Alleles at the DGAT1 Locus Better Explains a Quantitative Trait Locus With Major Effect on Milk Fat Content in Cattle , 2004, Genetics.

[6]  Gonçalo R. Abecasis,et al.  The Sequence Alignment/Map format and SAMtools , 2009, Bioinform..

[7]  Revisiting the “a posteriori” granddaughter design , 2015 .

[8]  Michel Georges,et al.  Genetic and functional confirmation of the causality of the DGAT1 K232A quantitative trait nucleotide in affecting milk yield and composition. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[9]  Nancy F. Hansen,et al.  Accurate Whole Human Genome Sequencing using Reversible Terminator Chemistry , 2008, Nature.

[10]  James M Reecy,et al.  Evaluation of variant identification methods for whole genome sequencing data in dairy cattle , 2014, BMC Genomics.

[11]  J. Weller,et al.  Identification of a missense mutation in the bovine ABCG2 gene with a major effect on the QTL on chromosome 6 affecting milk yield and composition in Holstein cattle. , 2005, Genome research.

[12]  P M VanRaden,et al.  Detection of quantitative trait loci affecting milk production, health, and reproductive traits in Holstein cattle. , 2004, Journal of dairy science.

[13]  P. VanRaden,et al.  Distribution and location of genetic effects for dairy traits. , 2009, Journal of dairy science.

[14]  Application of the a posteriori granddaughter design to the Holstein genome. , 2014, Animal : an international journal of animal bioscience.

[15]  R. Fries,et al.  Association of a lysine-232/alanine polymorphism in a bovine gene encoding acyl-CoA:diacylglycerol acyltransferase (DGAT1) with variation at a quantitative trait locus for milk fat content , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[16]  Positional candidate cloning of a QTL in dairy cattle: identification of a missense mutation in the bovine DGAT1 gene with major effect on milk yield and composition. , 2002 .

[17]  J. Weller,et al.  From QTL to QTN identification in livestock--winning by points rather than knock-out: a review. , 2007, Animal genetics.

[18]  P. VanRaden,et al.  Genomic evaluations with many more genotypes , 2011, Genetics Selection Evolution.

[19]  P. VanRaden,et al.  Efficient methods to compute genomic predictions. , 2008, Journal of dairy science.

[20]  Michel Georges,et al.  Molecular dissection of a quantitative trait locus: a phenylalanine-to-tyrosine substitution in the transmembrane domain of the bovine growth hormone receptor is associated with a major effect on milk yield and composition. , 2002, Genetics.

[21]  R. Snell,et al.  Sequence-based Association Analysis Reveals an MGST1 eQTL with Pleiotropic Effects on Bovine Milk Composition , 2016, Scientific Reports.

[22]  F. Miglior,et al.  Selection indices in Holstein cattle of various countries. , 2005, Journal of dairy science.

[23]  P. VanRaden,et al.  Identification of a nonsense mutation in APAF1 that is likely causal for a decrease in reproductive efficiency in Holstein dairy cattle. , 2016, Journal of dairy science.

[24]  Pablo Cingolani,et al.  © 2012 Landes Bioscience. Do not distribute. , 2022 .

[25]  M. Soller,et al.  Power of daughter and granddaughter designs for determining linkage between marker loci and quantitative trait loci in dairy cattle. , 1990, Journal of dairy science.

[26]  Hans H. Cheng,et al.  Coordinated international action to accelerate genome-to-phenome with FAANG, the Functional Annotation of Animal Genomes project , 2015, Genome Biology.

[27]  H. Thomsen,et al.  The DGAT1 K232A mutation is not solely responsible for the milk production quantitative trait locus on the bovine chromosome 14. , 2004, Journal of dairy science.

[28]  Richard Durbin,et al.  Sequence analysis Fast and accurate short read alignment with Burrows – Wheeler transform , 2009 .

[29]  R. N. Curnow,et al.  Estimating the locations and the sizes of the effects of quantitative trait loci using flanking markers , 1992, Theoretical and Applied Genetics.

[30]  J. Weller,et al.  Paternity validation and estimation of genotyping error rate for the BovineSNP50 BeadChip. , 2010, Animal genetics.

[31]  T. Mackay.  The genetic architecture of quantitative traits. , 2001, Annual review of genetics.

[32]  J. Weller,et al.  Invited review: quantitative trait nucleotide determination in the era of genomic selection. , 2011, Journal of dairy science.

[33]  K. Kemper,et al.  How old are quantitative trait loci and how widely do they segregate? , 2015, Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie.

[34]  J. Nadeau,et al.  Finding Genes That Underlie Complex Traits , 2002, Science.

[35]  T. Strom,et al.  Comparison among three variant callers and assessment of the accuracy of imputation from SNP array data to whole-genome sequence level in chicken , 2015, BMC Genomics.

[36]  David R. Kelley,et al.  A whole-genome assembly of the domestic cow, Bos taurus , 2009, Genome Biology.

[37]  E. Lander,et al.  Genetic dissection of complex traits: guidelines for interpreting and reporting linkage results , 1995, Nature Genetics.

[38]  Paul M. VanRaden,et al.  Changes in genetic selection differentials and generation intervals in US Holstein dairy cattle as a result of genomic selection , 2016, Proceedings of the National Academy of Sciences.

[39]  J. Weller,et al.  Fine Mapping of a QTL for Fertility on BTA7 and Its Association With a CNV in the Israeli Holsteins , 2011, G3: Genes | Genomes | Genetics.

[40]  Miki Ohira,et al.  LMO3 interacts with neuronal transcription factor, HEN2, and acts as an oncogene in neuroblastoma. , 2005, Cancer research.

[41]  R. Veerkamp,et al.  Genomic prediction from whole genome sequence in livestock: the 1000 Bull Genomes Project , 2014 .