Biology subjects

Garrick, D.

Publications and source records attributed to Garrick, D..

8 recordsLinked to original sources

bioRxiv2022

Distinct Subsets of Multi-Lymphoid Progenitors Support Ontogeny-Related Changes in Human Lymphopoiesis

Changes in lymphocyte production patterns occurring across human ontogeny remain poorly defined. In this study, we demonstrate that human lymphopoiesis is supported by three waves of embryonic, fetal, and postnatal multi-lymphoid progenitors (MLPs) differing in CD7 and CD10 expression and their output of CD127-/+ early lymphoid progenitors (ELP). Our results reveal that, like the fetal-to-adult switch in erythropoiesis, transition to postnatal life coincides with a shift from multilineage to B lineage-biased lymphopoiesis and an increase in production of CD127+ ELPs which persists until puberty. A further developmental transition is observed in elderly individuals where B-cell differentiation bypasses the CD127+ compartment and branches directly from CD10+ MLPs. Functional analyses indicate that these changes are determined at the level of the hematopoietic stem cell. Besides reconciling controversies about the identity and function of human MLPs, these results may shed light on the causes of age-related differences in the incidence of lymphoblastic leukemia.

immunology↗

bioRxiv2021

Non-additive QTL mapping of lactation traits in 124,000 sequence-imputed cattle reveals novel recessive loci

Deleterious recessive conditions have primarily been studied in a Mendelian disease context. Recently, several large effect, deleterious recessive mutations were discovered via non-additive GWAS of quantitative growth and developmental traits in cattle. This showed quantitative traits can be used as proxies of genetic disorders if they are indicative of whole animal health status and susceptible to underlying genetic conditions. Lactation traits might also reflect genetic disorders in cattle, given the increased energy demands of lactation and the substantial stresses imposed on the animal. Here, we report a screen of over 124,000 cows for recessive effects based on lactation traits. We discovered novel loci associated with five large recessive impacts on milk yield traits represented by missense variants (DOCK8, IL4R, KIAA0556, and SLC25A4) or premature stop variants (ITGAL, LRCH4, and RBM34) as candidate causal mutations. On milk composition traits, we identified several small effect dominance contributions to previously reported additive QTL. In contrasting analyses of milk yield and milk composition phenotypes, we note differing genetic architectures. Milk yield phenotypes presented lower heritabilities and fewer additive QTL, but higher non-additive genetic variance and a higher proportion of loci exhibiting dominance compared to milk composition phenotypes. Large-effect recessive QTL are segregating at surprisingly high frequencies in cattle. We speculate that the differences in genetic architecture between milk yield and milk composition phenotypes derive from underlying dissimilarities in the cellular and molecular representation of these traits. Lactation yields may act as a better proxy than milk composition traits for a wide range of underlying biological disorders affecting animal fitness

genetics↗

bioRxiv2021

HandyCNV: Standardized Summary, Annotation, Comparison, and Visualization of CNV, CNVR and ROH

Here we present an R package for summarizing, annotating, converting, comparing and visualizing CNV (copy number variants) and ROH (runs of homozygosity) detected from SNP (single nucleotide polymorphism) genotyping data. This one-stop post-analysis system is standardized, comprehensive, reproducible, timesaving and user friendly for research in humans and most diploid livestock species. Availability and ImplementationThe source code, demo data and vignettes can be found at https://github.com/JH-Zhou/HandyCNV

bioinformatics↗

bioRxiv2021

The genomes of precision edited cloned calves show no evidence for off-target events or increased de novo mutagenesis

Animal health and welfare are at the forefront of public concern and the agricultural sector is responding by prioritising the selection of welfare-relevant traits in their breeding schemes. In some cases, welfare-enhancing traits such as horn-status (i.e., polled) or diluted coat colour, which could enhance heat tolerance, may not segregate in breeds of primary interest, highlighting gene-editing tools such as the CRISPR-Cas9 technology as an approach to rapidly introduce variation into these populations. A major limitation preventing the acceptance of CRISPR-Cas9 mediated gene-editing, however, is the potential for off-target mutagenesis, which has raised concerns about the safety and ultimate applicability of this technology. Here, we present a clone-based study design that has allowed a detailed investigation of off-target and de novo mutagenesis in a cattle line bearing edits in the PMEL gene for diluted coat-colour. No off-target events were detected from high depth whole genome sequencing performed in precursor cell-lines and resultant calves cloned from those edited and non-edited cell lines. Long molecule sequencing at the edited site and plasmid-specific PCRs did not reveal structural variations and/or plasmid integration events in edited samples. Furthermore, an in-depth analysis of de novo mutations across samples revealed that the mutation frequency and spectra were unaffected by editing status. Cells in culture, however, had a distinct mutation signature where de novo mutations were predominantly C>A mutations, and in cloned calves they were predominantly T>G mutations, deviating from the expected excess of C>T mutations. We conclude that the gene-edited cells and calves in this study did not present a higher mutation load than unedited controls. Cell culture and somatic cell nuclear transfer cloning processes contributed the major source of contrast in mutational profile between samples.

genomics↗

bioRxiv2020

Identification of MAZ as a novel transcription factor regulating erythropoiesis

Erythropoiesis requires a combination of ubiquitous and tissue-specific transcription factors. Here, through DNA affinity purification followed by mass spectrometry, we have identified the widely expressed protein MAZ (Myc-associated zinc finger) as a transcription factor that binds to the promoter of the erythroid-specific human -globin gene. Genome-wide mapping in primary human erythroid cells revealed that MAZ also occupies active promoters as well as GATA1-bound enhancer elements of key erythroid genes. Consistent with an important role during erythropoiesis, knockdown of MAZ in primary human erythroid cells impairs erythroid differentiation, and genetic variants in the MAZ locus are associated with clinically important human erythroid traits. Taken together, these findings reveal the Zinc-finger transcription factor MAZ to be a previously unrecognised regulator of the erythroid differentiation program.

molecular biology↗

bioRxiv2019

Exact Distribution of Linkage Disequilibrium in the Presence of Mutation, Selection or Minor Allele Frequency Filtering

Linkage disequilibrium (LD), often expressed in terms of the squared correlation (r2) between allelic values at two loci, is an important concept in many branches of genetics and genomics. Genetic drift and recombination have opposite effects on LD, and thus r2 will keep changing until the effects of these two forces are counterbalanced. Several approximations have been used to determine the expected value of r2 at equilibrium in the presence or absence of mutation. In this paper, we propose a probability-based approach to compute the exact distribution of allele frequencies at two loci in a finite population at any generation t conditional on the distribution at generation t - 1. As r2 is a function of this distribution of allele frequencies, this approach can be used to examine the distribution of r2 over generations as it approaches equilibrium. The exact distribution of LD from our method is used to describe, quantify and compare LD at different equilibria, including equilibrium in the absence or presence of mutation, selection, and filtering by minor allele frequency. We also propose a deterministic formula for expected LD in the presence of mutation at equilibrium based on the exact distribution of LD.

genetics↗

bioRxiv2017

Parallel Computing to Speed up Whole-Genome Bayesian Regression Analyses Using Orthogonal Data Augmentation

1 AbstractBayesian multiple regression methods are widely used in whole-genome analyses to solve the problem that the number p of marker covariates is usually larger than the number n of observations. Inferences from most Bayesian methods are based on Markov chain Monte Carlo methods, where statistics are computed from a Markov chain constructed to have a stationary distribution equal to the posterior distribution of the unknown parameters. In practice, chains of about fifty thousand steps are typically used in whole-genome Bayesian regression analyses, which is computationally intensive. In this paper, we have shown how the sampling of marker effects can be made independent within each step of the chain. This is done by augmenting the marker covariate matrix by adding p new rows to it such that columns of the augmented marker covariate matrix are orthogonal. The phenotypes corresponding to the augmented rows of marker covariate matrix are considered missing. Ideally, the computations at each step of the MCMC chain, can be speeded up by the number k of computer processors up to the number p of markers. Addressing the heavy computational burden associated with Bayesian methods by parallel computing will lead to greater use of these methods.

genetics↗

bioRxiv2017

Multiple-trait Bayesian Regression Methods with Mixture Priors for Genomic Prediction

Bayesian multiple-regression methods incorporating different mixture priors for marker effects are widely used in genomic prediction. Improvement in prediction accuracies from using those methods, such as BayesB, BayesC and BayesC{pi}, have been shown in single-trait analyses with both simulated data and real data. These methods have been extended to multi-trait analyses, but only under a specific limited circumstance that assumes a locus affects all the traits or none of them. In this paper, we develop and implement the most general multi-trait BayesC{Pi} and BayesB methods allowing a broader range of mixture priors. Further, we compare them to single-trait methods and the \"restricted\" multi-trait formulation using real data. In those data analyses, significant higher prediction accuracies were sometimes observed from these new broad-based multi-trait Bayesian multiple-regression methods. The software tool JWAS offers routines to perform the analyses.

genetics↗