Research Note: Phenotypic trends for the multigenerational advanced intercross of the Virginia body weight lines of chickens

Random samples from generation S41 of the Virginia high and low 8-week body weight lines formed the base population for producing a multigenerational reciprocal intercross population. Although genetic mapping from this intercross has been reported, lacking are phenotypic trends across multiple generations. Here, we provide phenotypic information for the parental base population, the F1 reciprocal cross, and subsequent segregating recombinant generations F2 to F17. Heterosis for the selected trait in the F1 was negative for both reciprocal crosses. Phenotypic correlations for the selected trait in the recombinant generations were essentially nil for both males and females as was percent sexual dimorphism and coefficients of variation.

Resequencing of a Pekin duck breeding population provides insights into the genomic response to short-term artificial selection

BACKGROUND

Short-term, intense artificial selection drives fast phenotypic changes in domestic animals and leaves imprints on their genomes. However, the genetic basis of this selection response is poorly understood. To better address this, we employed the Pekin duck Z2 pure line, in which the breast muscle weight was increased nearly 3-fold after 10 generations of breeding. We denovo assembled a high-quality reference genome of a female Pekin duck of this line (GCA_003850225.1) and identified 8.60 million genetic variants in 119 individuals among 10 generations of the breeding population.

RESULTS

We identified 53 selected regions between the first and tenth generations, and 93.8% of the identified variations were enriched in regulatory and noncoding regions. Integrating the selection signatures and genome-wide association approach, we found that 2 regions covering 0.36 Mb containing UTP25 and FBRSL1 were most likely to contribute to breast muscle weight improvement. The major allele frequencies of these 2 loci increased gradually with each generation following the same trend. Additionally, we found that a copy number variation region containing the entire EXOC4 gene could explain 1.9% of the variance in breast muscle weight, indicating that the nervous system may play a role in economic trait improvement.

CONCLUSIONS

Our study not only provides insights into genomic dynamics under intense artificial selection but also provides resources for genomics-enabled improvements in duck breeding.

On the hidden temporal dynamics of plant adaptation

Adaptation to a wide range of environments is a major driver of plant diversity. It is now possible to catalog millions of potential adaptive genomic differences segregating between environments within a plant species in a single experiment. Understanding which of these changes contributes to adaptive phenotypic divergence between plant populations is a major goal of evolutionary biologists and crop breeders. In this review, we briefly highlight the approaches frequently used to understand the genetic basis of adaptive phenotypes in plants, and we discuss some of the limitations of these methods. We propose that direct observation of the process of adaptation using multigenerational studies and whole genome sequencing is a crucial missing component of recent studies of plant adaptation because it complements several shortcomings of sampling-based techniques.

Low-coverage sequencing in a deep intercross of the Virginia body weight lines provides insight to the polygenic genetic architecture of growth: novel loci revealed by increased power and improved genome-coverage

Genetic dissection of highly polygenic traits is a challenge, in part due to the power necessary to confidently identify loci with minor effects. Experimental crosses are valuable resources for mapping such traits. Traditionally, genome-wide analyses of experimental crosses have targeted major loci using data from a single generation (often the F₂) with individuals from later generations being generated for replication and fine-mapping. Here, we aim to confidently identify minor-effect loci contributing to the highly polygenic basis of the long-term, bi-directional selection responses for 56-d body weight in the Virginia body weight chicken lines. To achieve this, a strategy was developed to make use of data from all generations (F₂-F₁₈) of the advanced intercross line, developed by crossing the low and high selected lines after 40 generations of selection. A cost-efficient low-coverage sequencing based approach was used to obtain high-confidence genotypes in 1Mb bins across 99.3% of the chicken genome for >3,300 intercross individuals. In total, 12 genome-wide significant, and 30 additional suggestive QTL reaching a 10% FDR threshold, were mapped for 56-d body weight. Only 2 of these QTL reached genome-wide significance in earlier analyses of the F₂ generation. The minor-effect QTL mapped here were generally due to an overall increase in power by integrating data across generations, with contributions from increased genome-coverage and improved marker information content. The 12 significant QTL explain >37% of the difference between the parental lines, three times more than 2 previously reported significant QTL. The 42 significant and suggestive QTL together explain >80%. Making integrated use of all available samples from multiple generations in experimental crosses are economically feasible using the low-cost, sequencing-based genotyping strategies outlined here. Our empirical results illustrate the value of this strategy for mapping novel minor-effect loci contributing to complex traits to provide a more confident, comprehensive view of the individual loci that form the genetic basis of the highly polygenic, long-term selection responses for 56-d body weight in the Virginia body weight chicken lines.

Are Copy Number Variations within the FecB Gene Significantly Associated with Morphometric Traits in Goats?

The Booroola fecundity (FecB) gene is a major fertility-related gene first identified in Booroola sheep. Numerous studies have investigated whether the FecB gene is a major fecundity gene in goats or whether there are other genes that play a critical role in goat fertility. Nevertheless, little attention has been paid to the role of the FecB gene in the body morphometric traits of goats, despite the positive relationship discerned between litter size and growth. We identified five copy number variations (CNVs) within the FecB gene in 641 goats, including 318 Shaanbei white cashmere (SBWC) goats, 203 Guizhou Heima (GZHM) goats, and 120 Nubian goats, which exhibited different distributions among these populations. Our results revealed that these five CNVs were significantly associated with goat morphometric traits (p < 0.05). The normal type of CNV3 was the dominant type and displayed superior phenotypes in both litter size and morphometric traits, making it an effective marker for goat breeding. Consequently, LD blocks in the region of 10 Mb upstream and downstream from FecB and potential transcription factors (TFs) that could bind with the CNVs were analyzed via bioinformatics. Although no significant LD block was detected, our results illustrated that these CNVs could bind to growth-related TFs and indirectly affect the growth development of the goats. We identified potential markers to promote litter size and growth, and we offer a theoretical foundation for further breeding work.

Assessment the effect of genomic selection and detection of selective signature in broilers

Due to high selection advances and shortened generation interval, genomic selection (GS) is now an effective animal breeding scheme. In broilers, many studies have compared the accuracy of different GS prediction methods, but few reports have demonstrated phenotypic or genetic changes using GS. In this study, the paternal chicken line B underwent continuous selection for 3 generations. The chicken 55 k SNP chip was used to estimate the genetic parameters and detect genomic response regions by selective sweep analysis. The heritability for body weight (BW), meat production, and abdominal fat traits were ranged from 0.12 to 0.38. A high genetic correlation was found between BW and meat production traits, while a low genetic correlation (<0.1) was found between meat production and abdominal fat traits. Selection resulted in an increase of about 516 g in BW and 140 g in breast muscle weight. Percentage of breast muscle and whole thigh were increased 0.8 to 1.5%. No change was observed in abdominal fat percentage. The genomic estimated breeding value advances was positive for BW and meat production (except whole thigh percentage), while negative for abdominal fat percentage. By selective sweep analysis, 39 common chromosomal regions and 102 protein coding genes were found to be influenced, including MYH1A, MYH1B, and MYH1D of the MYH gene family. Tight junction pathway as well as myosin complex related terms were enriched. This study demonstrates the effective use of GS for improvements in BW and meat production in chicken line B. Further, genomic regions, responsive to intensive genetic selection, were identified to contain genes of the MYH family.

Intestinal Microbiota and Host Cooperate for Adaptation as a Hologenome

Multiomic analyses reported here involved two lines of chickens, from a common founder population, that had undergone long-term selection for high (HWS) or low (LWS) 56-day body weight. In these lines that differ by around 15-fold in body weight, we observed different compositions of intestinal microbiota in the holobionts and variation in DNA methylation, mRNA expression, and microRNA profiles in the ceca. Insulin-like growth factor 2 mRNA-binding protein 1 (IGF2BP1) was the most upregulated gene in HWS ceca with its expression likely affected by the upregulation of expression of gga-miR-2128 and a methylated region near its transcription start site (388 bp). Correlation analysis showed that IGF2BP1 expression was associated with an abundance of microbes, such as Lactobacillus and Methanocorpusculum. These findings suggest that IGF2BP1 was regulated in the hologenome in adapting to long-term artificial selection for body weight. Our study provides evidence that adaptation of the holobiont can occur in the microbiome as well as in the epigenetic profile of the host.

IMPORTANCE The hologenome concept has broadened our perspectives for studying host-microbe coevolution. The multiomic analyses reported here involved two lines of chickens, from a common founder population, that had undergone long-term selection for high (HWS) or low (LWS) 56-day body weight. In these lines that differ by around 15-fold in body weight, we observed different compositions of intestinal microbiota in the holobionts, and variation in DNA methylation, mRNA expression, and microRNA profiles in ceca. The insulin-like growth factor 2 mRNA-binding protein 1 (IGF2BP1) was the most upregulated gene in HWS ceca with its expression likely affected by a methylated region near its transcription start site and the upregulation of expression of gga-miR-2128. Correlation analysis also showed that IGF2BP1 expression was associated with the abundance of microbes, such as Lactobacillus and Methanocorpusculum. These findings suggest that IGF2BP1 was regulated in the hologenome in response to long-term artificial selection for body weight. Our study shows that the holobiont may adapt in both the microbiome and the host's epigenetic profile.

Genome‑wide association study and genomic prediction for growth traits in yellow-plumage chicken using genotyping-by-sequencing

Background

Growth traits are of great importance for poultry breeding and production and have been the topic of extensive investigation, with many quantitative trait loci (QTL) detected. However, due to their complex genetic background, few causative genes have been confirmed and the underlying molecular mechanisms remain unclear, thus limiting our understanding of QTL and their potential use for the genetic improvement of poultry. Therefore, deciphering the genetic architecture is a promising avenue for optimising genomic prediction strategies and exploiting genomic information for commercial breeding. The objectives of this study were to: (1) conduct a genome-wide association study to identify key genetic factors and explore the polygenicity of chicken growth traits; (2) investigate the efficiency of genomic prediction in broilers; and (3) evaluate genomic predictions that harness genomic features.

Results

We identified five significant QTL, including one on chromosome 4 with major effects and four on chromosomes 1, 2, 17, and 27 with minor effects, accounting for 14.5 to 34.1% and 0.2 to 2.6% of the genomic additive genetic variance, respectively, and 23.3 to 46.7% and 0.6 to 4.5% of the observed predictive accuracy of breeding values, respectively. Further analysis showed that the QTL with minor effects collectively had a considerable influence, reflecting the polygenicity of the genetic background. The accuracy of genomic best linear unbiased predictions (BLUP) was improved by 22.0 to 70.3% compared to that of the conventional pedigree-based BLUP model. The genomic feature BLUP model further improved the observed prediction accuracy by 13.8 to 15.2% compared to the genomic BLUP model.

Conclusions

A major QTL and four minor QTL were identified for growth traits; the remaining variance was due to QTL effects that were too small to be detected. The genomic BLUP and genomic feature BLUP models yielded considerably higher prediction accuracy compared to the pedigree-based BLUP model. This study revealed the polygenicity of growth traits in yellow-plumage chickens and demonstrated that the predictive ability can be greatly improved by using genomic information and related features.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-021-00672-9.

The genetic architecture of temperature adaptation is shaped by population ancestry and not by selection regime

Background

Understanding the genetic architecture of temperature adaptation is key for characterizing and predicting the effect of climate change on natural populations. One particularly promising approach is Evolve and Resequence, which combines advantages of experimental evolution such as time series, replicate populations, and controlled environmental conditions, with whole genome sequencing. Recent analysis of replicate populations from two different Drosophila simulans founder populations, which were adapting to the same novel hot environment, uncovered very different architectures—either many selection targets with large heterogeneity among replicates or fewer selection targets with a consistent response among replicates.

Results

Here, we expose the founder population from Portugal to a cold temperature regime. Although almost no selection targets are shared between the hot and cold selection regime, the adaptive architecture was similar. We identify a moderate number of targets under strong selection (19 selection targets, mean selection coefficient = 0.072) and parallel responses in the cold evolved replicates. This similarity across different environments indicates that the adaptive architecture depends more on the ancestry of the founder population than the specific selection regime.

Conclusions

These observations will have broad implications for the correct interpretation of the genomic responses to a changing climate in natural populations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-021-02425-9.

Phenotypic Plasticity Contributes to Maize Adaptation and Heterosis

Plant phenotypic plasticity describes altered phenotypic performance of an individual when grown in different environments. Exploring genetic architecture underlying plant plasticity variation may help mitigate the detrimental effects of a rapidly changing climate on agriculture, but little research has been done in this area to date. In the present study, we established a population of 976 maize F₁ hybrids by crossing 488 diverse inbred lines with two elite testers. Genome-wide association study identified hundreds of quantitative trait loci associated with phenotypic plasticity variation across diverse F₁ hybrids, the majority of which contributed very little variance, in accordance with the polygenic nature of these traits. We identified several quantitative trait locus regions that may have been selected during the tropical-temperate adaptation process. We also observed heterosis in terms of phenotypic plasticity, in addition to the traditional genetic value differences measured between hybrid and inbred lines, and the pattern of which was affected by genetic background. Our results demonstrate a landscape of phenotypic plasticity in maize, which will aid in the understanding of its genetic architecture, its contribution to adaptation and heterosis, and how it may be exploited for future maize breeding in a rapidly changing environment.

The effects of the sex chromosomes on the inheritance of species-specific traits of the copulatory organ shape in Drosophila virilis and Drosophila lummei

The shape of the male genitalia in many taxa is the most rapidly evolving morphological structure, often driving reproductive isolation, and is therefore widely used in systematics as a key character to distinguish between sibling species. However, only a few studies have used the genital arch of the male copulatory organ as a model to study the genetic basis of species-specific differences in the Drosophila copulatory system. Moreover, almost nothing is known about the effects of the sex chromosomes on the shape of the male mating organ. In our study, we used a set of crosses between D. virilis and D. lummei and applied the methods of quantitative genetics to assess the variability of the shape of the male copulatory organ and the effects of the sex chromosomes and autosomes on its variance. Our results showed that the male genital shape depends on the species composition of the sex chromosomes and autosomes. Epistatic interactions of the sex chromosomes with autosomes and the species origin of the Y-chromosome in a male in interspecific crosses also influenced the expression of species-specific traits in the shape of the male copulatory system. Overall, the effects of sex chromosomes were comparable to the effects of autosomes despite the great differences in gene numbers between them. It may be reasonably considered that sexual selection for specific genes associated with the shape of the male mating organ prevents the demasculinization of the X chromosome.

Genetic Dissection of Growth Traits in a Unique Chicken Advanced Intercross Line

The advanced intercross line (AIL) that is created by successive generations of pseudo-random mating after the F₂ generation is a valuable resource, especially in agricultural livestock and poultry species, because it improves the precision of quantitative trait loci (QTL) mapping compared with traditional association populations by introducing more recombination events. The growth traits of broilers have significant economic value in the chicken industry, and many QTLs affecting growth traits have been identified, especially on chromosomes 1, 4, and 27, albeit with large confidence intervals that potentially contain dozens of genes. To promote a better understanding of the underlying genetic architecture of growth trait differences, specifically body weight and bone development, in this study, we report a nine-generation AIL derived from two divergent outbred lines: High Quality chicken Line A (HQLA) and Huiyang Bearded (HB) chicken. We evaluate the genetic architecture of the F₀, F₂, F₈, and F₉ generations of AIL and demonstrate that the population of the F₉ generation sufficiently randomized the founder genomes and has the characteristics of rapid linkage disequilibrium decay, limited allele frequency decline, and abundant nucleotide diversity. This AIL yielded a much narrower QTL than the F₂ generations, especially the QTL on chromosome 27, which was reduced to 120 Kb. An ancestral haplotype association analysis showed that most of the dominant haplotypes are inherited from HQLA but with fluctuation of the effects between them. We highlight the important role of four candidate genes (PHOSPHO1, IGF2BP1, ZNF652, and GIP) in bone growth. We also retrieved a missing QTL from AIL on chromosome 4 by identifying the founder selection signatures, which are explained by the loss of association power that results from rare alleles. Our study provides a reasonable resource for detecting quantitative trait genes and tracking ancestor history and will facilitate our understanding of the genetic mechanisms underlying chicken bone growth.

Multiple ancestral haplotypes harboring regulatory mutations cumulatively contribute to a QTL affecting chicken growth traits

In depth studies of quantitative trait loci (QTL) can provide insights to the genetic architectures of complex traits. A major effect QTL at the distal end of chicken chromosome 1 has been associated with growth traits in multiple populations. This locus was fine-mapped in a fifteen-generation chicken advanced intercross population including 1119 birds and explored in further detail using 222 sequenced genomes from 10 high/low body weight chicken stocks. We detected this QTL that, in total, contributed 14.4% of the genetic variance for growth. Further, nine mosaic precise intervals (Kb level) which contain ancestral regulatory variants were fine-mapped and we chose one of them to demonstrate the key regulatory role in the duodenum. This is the first study to break down the detail genetic architectures for the well-known QTL in chicken and provides a good example of the fine-mapping of various of quantitative traits in any species.

Haplotype Purging After Relaxation of Selection in Lines of Chickens that Had Undergone Long-Term Selection for High and Low Body Weight

Bi-directional selection for increased and decreased 56-day body weights (BW56) has been applied to two lines of White Plymouth Rock chickens—the Virginia high (HWS) and low (LWS) body weight lines. Correlated responses have been observed, including negative effects on traits related to fitness. Here, we use high and low body weight as proxies for fitness. On a genome-wide level, relaxed lines (HWR, LWR) bred from HWS and LWS purged some genetic variants in the selected lines. Whole-genome re-sequencing was here used to identify individual loci where alleles that accumulated during directional selection were purged when selection was relaxed. In total, 11 loci with significant purging signals were identified, five in the low (LW) and six in the high (HW) body weight lineages. Associations between purged haplotypes in these loci and BW56 were tested in an advanced intercross line (AIL). Two loci with purging signals and haplotype associations to BW56 are particularly interesting for further functional characterization, one locus on chromosome 6 in the LW covering the sour-taste receptor gene PKD2L1, a functional candidate gene for the decreased appetite observed in the LWS and a locus on chromosome 20 in the HW containing a skeletal muscle hypertrophy gene, DNTTIP1.

Dynamic genetic architecture of yeast response to environmental perturbation shed light on origin of cryptic genetic variation

Cryptic genetic variation could arise from, for example, Gene-by-Gene (G-by-G) or Gene-by-Environment (G-by-E) interactions. The underlying molecular mechanisms and how they influence allelic effects and the genetic variance of complex traits is largely unclear. Here, we empirically explored the role of environmentally influenced epistasis on the suppression and release of cryptic variation by reanalysing a dataset of 4,390 haploid yeast segregants phenotyped on 20 different media. The focus was on 130 epistatic loci, each contributing to segregant growth in at least one environment and that together explained most (69–100%) of the narrow sense heritability of growth in the individual environments. We revealed that the epistatic growth network reorganised upon environmental changes to alter the estimated marginal (additive) effects of the individual loci, how multi-locus interactions contributed to individual segregant growth and the level of expressed genetic variance in growth. The estimated additive effects varied most across environments for loci that were highly interactive network hubs in some environments but had few or no interactors in other environments, resulting in changes in total genetic variance across environments. This environmentally dependent epistasis was thus an important mechanism for the suppression and release of cryptic variation in this population. Our findings increase the understanding of the complex genetic mechanisms leading to cryptic variation in populations, providing a basis for future studies on the genetic maintenance of trait robustness and development of genetic models for studying and predicting selection responses for quantitative traits in breeding and evolution.

Many biological traits are polygenic, with complex interplay between underlying genes and the surrounding environment. As a result, individuals with the same allele might have distinctive phenotypes due to differences in the polygenic background and/or the environment. Such differences often create additional genetic variation that is highly relevant to quantitative and evolutionary genetics by limiting our ability to accurately predict the phenotypes in medical or agricultural applications and providing opportunities for long term evolution. Previously, yeast growth regulating genes were found to be organised in large interacting networks. Here, we found that these networks were reorganised upon environmental changes, and that this resulted in altered effect sizes of individual genes, and how the whole network contributed to growth and the level of total genetic variance, providing a basis for future studies on the genetic maintenance of trait robustness and development of genetic models for studying and predicting selection responses for quantitative traits.

Bidirectional Selection for Body Weight on Standing Genetic Variation in a Chicken Model

Experimental populations of model organisms provide valuable opportunities to unravel the genomic impact of selection in a controlled system. The Virginia body weight chicken lines represent a unique resource to investigate signatures of selection in a system where long-term, single-trait, bidirectional selection has been carried out for more than 60 generations. At 55 generations of divergent selection, earlier analyses of pooled genome resequencing data from these lines revealed that 14.2% of the genome showed extreme differentiation between the selected lines, contained within 395 genomic regions. Here, we report more detailed analyses of these data exploring the regions displaying within- and between-line genomic signatures of the bidirectional selection applied in these lines. Despite the strict selection regime for opposite extremes in body weight, this did not result in opposite genomic signatures between the lines. The lines often displayed a duality of the sweep signatures, where an extended region of homozygosity in one line, in contrast to mosaic pattern of heterozygosity in the other line. These haplotype mosaics consisted of short, distinct haploblocks of variable between-line divergence, likely the results of a complex demographic history involving bottlenecks, introgressions and moderate inbreeding. We demonstrate this using the example of complex haplotype mosaicism in the growth1 QTL. These mosaics represent the standing genetic variation available at the onset of selection in the founder population. Selection on standing genetic variation can thus result in different signatures depending on the intensity and direction of selection.

Integrating Selection Mapping With Genetic Mapping and Functional Genomics

Genomic scans for signatures of selection allow us to, in principle, detect variants and genes that underlie recent adaptations. By combining selection mapping with genetic mapping of traits known to be relevant to adaptation, we can simultaneously investigate whether genes and variants show signals of recent selection and whether they impact traits that have likely been selected. There are three ways to integrate selection mapping with genetic mapping or functional genomics: (1) To use genetic mapping data from other populations as a form of genome annotation. (2) To perform experimental evolution or artificial selection to be able to study selected variants when they segregate, either by performing genetic mapping before selection or by crossing the selected individuals to some reference population. (3) To perform a comparative study of related populations facing different selection regimes. This short review discusses these different ways of integrating selection mapping with genetic mapping and functional genomics, with examples of how each has been done.