Genome-wide Selection Research Articles

Genome-wide selection of potential target candidates for RNAi against Nilaparvata lugens

BackgroundNilaparvata lugens is one of the most destructive pests of rice. RNAi-based N. lugens control offers one alternative strategy to traditional chemical insecticides. However, selection of potential target for RNAi against N. lugens remains a major challenge. Only two target genes for nuclear transgenic N. lugens-resistant plants have been screened. Importantly, only one or few potential target genes against N. lugens were screened every time by knowledge of essential genes from model organisms in previous study.ResultsHere, in silico genome-wide selection of potential target genes against N. lugens through homology comparison was performed. Through genome synteny comparisons, about 3.5% of Drosophila melanogaster genome was found to have conserved genomic synteny with N. lugens genome. By using N. lugens proteins to search D. melanogaster homologs defining lethal or sterile phenotype, 358 N. lugens genes were first screened as putative target genes. Transgenic rice lines expressing dsRNA of randomly selected gene (NlRan or NlSRP54) from 358 putative target genes enhanced resistance to N. lugens. After expression check and safety check, 115 N. lugens genes were screened as potential target candidates.ConclusionThe combined efforts in this study firstly provide one in silico genome-wide homology-based screening approach for RNAi-based target genes against N. lugens, which not only offer one new opportunity to batch select potential target candidates in pests of interest, but also will facilitate the selection of RNAi target in many pest species by providing more than one hundred potential target candidates.

Genomic Insights into Pig Domestication and Adaptation: An Integrated Approach Using Genome-Wide Selection Analysis and Multiple Public Datasets

As a global focus of animal husbandry, pigs provide essential meat resources for humans. Therefore, analyzing the genetic basis of adaptability, domestication, and artificial selection in pigs will contribute to further breeding. This study performed a genome-wide selection sweep analysis to identify candidate genes related to domestication and adaptive selection via data from 2413 public genotypes. Two complementary statistical analyses, FST (fixation index) and XP–EHH (cross–population extended haplotype homozygosity) were applied. The results revealed that numerous candidate genes were associated with high-altitude adaptability (e.g., SIRPA, FRS2, and GRIN2B) and habitat temperature adaptability (e.g., MITF, PI3KC2A, and FRS2). In addition, candidate genes related to the domestic genetic imprint of indigenous pigs (e.g., TNR, NOCT, and SPATA5) and strong artificial selection pressure in commercial breeds (e.g., ITPR2, HSD17B12, and UGP2) were identified in this study. Specifically, some MHC–related genes (e.g., ZRTB12, TRIM26, and C7H6orf15) were also under selection during domestication and artificial selection. Additionally, a phylogenetic comparative analysis revealed that the genetic divergence between populations does not fully follow the geographical distribution and management history in the major histocompatibility complex region/major histocompatibility complex II haplotypes, unlike that of the genome-wide genotypes. Furthermore, the higher heterozygosity and haplotype alleles of MHC reduce the differences between populations. Briefly, this study not only helps promote the relative theoretical understanding of environmental adaptive selection and domestication but also provides a theoretical reference for disease-resistant breeding in pigs.

Genetic Adaptations of the Tibetan Pig to High-Altitude Hypoxia on the Qinghai-Tibet Plateau.

The Tibetan Plateau's distinctive high-altitude environment, marked by extreme cold and reduced oxygen levels, presents considerable survival challenges for both humans and mammals. Natural selection has led to the accumulation of adaptive mutations in Tibetan pigs, enabling them to develop distinctive adaptive phenotypes. Here, we aim to uncover the genetic mechanisms underlying the adaptation of Tibetan pigs to high-altitude hypoxia. Therefore, we conducted a systematic analysis of 140 whole-genome sequencing (WGS) data points from different representing pig populations. Our analysis identified a total of 27,614,561 mutations, including 22,386,319 single-nucleotide variants (SNVs) and 5,228,242 insertions/deletions (INDELs, size < 50 bp). A total of 11% (2,678,569) of the SNVs were newly identified in our project, significantly expanding the dataset of genetic variants in Tibetan pigs. Compared to other pig breeds, Tibetan pigs are uniquely adapted to high-altitude environments, exhibiting the highest genetic diversity and the lowest inbreeding coefficient. Employing the composite of multiple signals (CMS) method, we scanned the genome-wide Darwinian positive selection signals and identified 32,499 Tibetan pig positively selected SNVs (TBPSSs) and 129 selected genes (TBPSGs), including 213 newly discovered genes. Notably, we identified eight genes (PHACTR1, SFI1, EPM2A, SLC30A7, NKAIN2, TNNI3K, and PLIN2) with strong nature selection signals. They are likely to improve cardiorespiratory function and fat metabolism to help Tibetan pigs become adapted to the high-altitude environment. These findings provide new insights into the genetic mechanisms of high-altitude adaptation and the adaptive phenotypes of Tibetan pigs.

Phylogenetic Relations and High-Altitude Adaptation in Wild Boar (Sus scrofa), Identified Using Genome-Wide Data.

The Qinghai-Tibet Plateau (QTP) wild boar is an excellent model for investigating high-altitude adaptation. In this study, we analyzed genome-wide data from 93 wild boars compiled from various studies worldwide, including the QTP, southern and northern regions of China, Europe, Northeast Asia, and Southeast Asia, to explore their phylogenetic patterns and high-altitude adaptation based on genome-wide selection signal analysis and run of homozygosity (ROH) estimation. The findings demonstrate the alignment between the phylogenetic associations among wild boars and their geographical location. An ADMIXTURE analysis indicated a relatively close genetic relationship between QTP and southern Chinese wild boars. Analyses of the fixation index and cross-population extended haplotype homozygosity between populations revealed 295 candidate genes (CDGs) associated with high-altitude adaptation, such as TSC2, TELO2, SLC5A1, and SLC5A4. These CDGs were significantly overrepresented in pathways such as the mammalian target of rapamycin signaling and Fanconi anemia pathways. In addition, 39 ROH islands and numerous selective CDGs (e.g., SLC5A1, SLC5A4, and VCP), which are implicated in glucose metabolism and mitochondrial function, were discovered in QTP wild boars. This study not only assessed the phylogenetic history of QTP wild boars but also advanced our comprehension of the genetic mechanisms underlying the adaptation of wild boars to high altitudes.

Phenotypic evidence of deltamethrin resistance and identification of selective sweeps in Anopheles mosquitoes on the Bijagós Archipelago, Guinea-Bissau

Vector control in the Bijagós Archipelago of Guinea-Bissau currently relies on pyrethroid insecticide-treated nets. However, data on insecticide resistance in Guinea-Bissau is limited. This study identified deltamethrin resistance in the Anopheles gambiae sensu lato complex on Bubaque island using WHO tube tests in November 2022. Whole genome sequencing of An. gambiae sensu stricto mosquitoes identified six single nucleotide polymorphisms (SNPs) previously associated with, or putatively associated with, insecticide resistance: T791M, L995F, N1570Y, A1746S and P1874L in the vgsc gene, and L119V in the gste2 gene. Twenty additional non-synonymous SNPs were identified in insecticide-resistance associated genes. Four of these SNPs were present at frequencies over 5% in the population: T154S, I126F and G26S in the vgsc gene and A65S in ace1. Genome wide selection scans using Garud’s H12 statistic identified two selective sweeps: one in chromosome X and one in chromosome 2R. Both selective sweeps overlap with metabolic genes previously associated with insecticide resistance, including cyp9k1 and the cyp6aa/cyp6p gene cluster. This study presents the first phenotypic testing for deltamethrin resistance and the first whole genome sequence data for Anophelesgambiae mosquitoes from the Bijagós, contributing data of significance for vector control policy in this region.

Population Genomics of Plasmodium malariae from Four African Countries.

Plasmodium malariae is geographically widespread but neglected and may become more prevalent as P. falciparum declines. We completed the largest genomic study of African P. malariae to-date by performing hybrid capture and sequencing of 77 isolates from Cameroon (n=7), the Democratic Republic of the Congo (n=16), Nigeria (n=4), and Tanzania (n=50) collected between 2015 and 2021. There is no evidence of geographic population structure. Nucleotide diversity was significantly lower than in co-localized P. falciparum isolates, while linkage disequilibrium was significantly higher. Genome-wide selection scans identified no erythrocyte invasion ligands or antimalarial resistance orthologs as top hits; however, targeted analyses of these loci revealed evidence of selective sweeps around four erythrocyte invasion ligands and six antimalarial resistance orthologs. Demographic inference modeling suggests that African P. malariae is recovering from a bottleneck. Altogether, these results suggest that P. malariae is genomically atypical among human Plasmodium spp. and panmictic in Africa.

Genome-Wide Selection Sweep Analysis to Identify Candidate Genes with Black and Brown Color in Tibetan Sibu Yaks.

Although coat color is an important economic phenotype in domesticated yaks (Bos grunniens), its genetic basis is not yet fully understood. In this study, a genome-wide selective sweep and high-frequency runs of homozygosity (ROH) identification were performed on 50 yaks with different coat colors to investigate candidate genes (CDGs) related to coat color. The results suggested that 2263 CDGs were identified from the 5% interaction windows of the FST and θπ ratio, along with 2801 and 2834 CDGs from black and brown yaks with iHS, respectively. Furthermore, 648 and 691 CDGs from black and brown yaks, which were widely enriched in pathways related to melanogenesis, melanocyte differentiation, and melanosome organization via GO and KEGG functional enrichment, respectively, were confirmed on the basis of the intersection of three parameters. Additionally, the genome of brown yaks presented more ROH, longer ROH fragments, and higher inbreeding levels than those of black yaks. Specifically, a large number of genes related to melanin synthesis and regulation (e.g., UST, TCF25, and AHRR) from the ROH islands were confirmed to be under strong selection. In summary, the results of this study enhance the understanding of the genetic basis for determining yak coat color.

Comparative Genomics Supports Ecologically Induced Selection as a Putative Driver of Banded Penguin Diversification.

The relative importance of genetic drift and local adaptation in facilitating speciation remains unclear. This is particularly true for seabirds, which can disperse over large geographic distances, providing opportunities for intermittent gene flow among distant colonies that span the temperature and salinity gradients of the oceans. Here, we delve into the genomic basis of adaptation and speciation of banded penguins, Galápagos (Spheniscus mendiculus), Humboldt (Spheniscus humboldti), Magellanic (Spheniscus magellanicus), and African penguins (Spheniscus demersus), by analyzing 114 genomes from the main 16 breeding colonies. We aim to identify the molecular mechanism and genomic adaptive traits that have facilitated their diversifications. Through positive selection and gene family expansion analyses, we identified candidate genes that may be related to reproductive isolation processes mediated by ecological thermal niche divergence. We recover signals of positive selection on key loci associated with spermatogenesis, especially during the recent peripatric divergence of the Galápagos penguin from the Humboldt penguin. High temperatures in tropical habitats may have favored selection on loci associated with spermatogenesis to maintain sperm viability, leading to reproductive isolation among young species. Our results suggest that genome-wide selection on loci associated with molecular pathways that underpin thermoregulation, osmoregulation, hypoxia, and social behavior appears to have been crucial in local adaptation of banded penguins. Overall, these results contribute to our understanding of how the complexity of biotic, but especially abiotic, factors, along with the high dispersal capabilities of these marine species, may promote both neutral and adaptive lineage divergence even in the presence of gene flow.

Genomic analyses identify 15 susceptibility loci and reveal HDAC2, SOX2-OT, and IGF2BP2 in a naturally-occurring canine model of gastric cancer.

Gastric cancer (GC) is the fifth most common human cancer worldwide, but the genetic etiology is largely unknown. We performed a Bayesian genome-wide association study and selection analyses in a naturally-occurring canine model of GC, the Belgian Tervuren and Sheepdog breeds, to elucidate underlying genetic risk factors. We identified 15 loci with over 90% predictive accuracy for the GC phenotype. Variant filtering revealed germline putative regulatory variants for the EPAS1 (HIF2A) and PTEN genes and a coding variant in CD101. Although closely related to Tervuren and Sheepdogs, Belgian Malinois rarely develop GC. Across-breed analyses uncovered protective haplotypes under selection in Malinois at SOX2-OT and IGF2BP2. Among Tervuren and Sheepdogs, HDAC2 putative regulatory variants were present at comparatively high frequency and were associated with GC. Here, we describe a complex genetic architecture governing GC in a dog model, including genes such as PDZRN3, that have not been associated with human GC.

Predictions in biometric models

One of the domains of genetic enhancement that has extensively employed both simulation and authentic data is Biometrics. Selecting efficient models for the Genome-Wide Selection (GWS) process using molecular markers (SNPs) presents several challenges. Among these challenges is the effective identification of the optimal model for fitting a given dataset. To contribute to this endeavor, this paper's primary objective is to assess the predictive accuracy of nine (9) distinct models, each following different paradigms within the realm of Biometrics. The data employed in this study were generated through simulation, encompassing the primary issues encountered in this field of research, including high dimensionality, nonlinearity, and multicollinearity. As the primary findings, notable observations include the enhancement of predictive efficiency as data noise decreases, the predominance of the tree paradigm (for low noise levels, BOO), and the efficacy of the neural network paradigm (for high noise levels, RBF).

Extreme genetic signatures of local adaptation in a notorious rice pest, Chilo suppressalis

ABSTRACT Climatic variation stands as a significant driving force behind genetic differentiation and the evolution of adaptive traits. Chilo (C.) suppressalis, commonly known as the rice stem borer, is a highly destructive pest that crucially harms rice production. The lack of natural population genomics data has hindered a more thorough understanding of its climate adaptation, particularly the genetic basis underlying adaptive traits. To overcome this obstacle, our study employed completely resequenced genomes of 384 individuals to explore the population structure, demographic history, and gene flow of C. suppressalis in China. This study observed that its gene flow occurred asymmetrically, moving from central populations to peripheral populations. Using genome-wide selection scans and genotype-environment association studies, we identified potential loci that may be associated with climatic adaptation. The most robust signal was found to be associated with cold tolerance, linked to a homeobox gene, goosecoid (GSC), whose expression level was significantly different in low and high latitudes. Moreover, downregulating the expression of this gene by RNAi enhances its cold tolerance phenotypes. Our findings have uncovered and delved into the genetic foundation of the ability of C. suppressalis to adapt to its environment. This is essential in ensuring the continued effectiveness and sustainability of novel control techniques.

Genome-wide selection reveals candidate genes associated with multiple teats in Hu sheep

Increasing the number of teats in sheep helps to improve the survival rate of sheep lambs after birth. In order to analyze the candidate genes related to the formation of multiple teats in Hu sheep, the present study was conducted to investigate the genetic pattern of multiple teats in Hu sheep. In this study, based on genome-wide data from 157 Hu sheep, Fst, xp-EHH, Pi and iHS signaling were performed, and the top 5% signal regions of each analyzed result were annotated based on the Oar_v4.0 for sheep. The results show that a total of 142 SNP loci were selected. We found that PTPRG, TMEM117 and LRP1B genes were closely associated with polypodium formation in Hu sheep, in addition, among the candidate genes related to polypodium we found genes such as TMEM117, SLC25A21 and NCKAP5 related to milk traits. The present study screened out candidate genes for the formation of multiple teats at the genomic level in Hu sheep.

Multiomic meta-analysis suggests a correlation between steroid hormone-related genes and litter size in goats.

Litter size is a key indicator of production performance in livestock. However, its genetic basis in goats remains poorly understood. In this work, a genome-wide selection sweep analysis (GWSA) on 100 published goat genomes with different litter rates was performed for the first time to identify candidate genes related to kidding rate. This analysis was combined with the public RNA-sequencing data of ovary tissues (follicular phase) from high- and low-yielding goats. A total of 2278 genes were identified by GWSA. Most of these genes were enriched in signaling pathways related to ovarian follicle development and hormone secretion. Moreover, 208 differentially expressed genes between groups were obtained from the ovaries of goats with different litter sizes. These genes were substantially enriched in the cholesterol and steroid synthesis signaling pathways. Meanwhile, the weighted gene co-expression network was used to perform modular analysis of differentially expressed genes. The results showed that seven modules were reconstructed, of which one module showed a very strong correlation with litter size (r = -0.51 and p-value <0.001). There were 51 genes in this module, and 39 hub genes were screened by Pearson's correlation coefficient between core genes > 0.4, correlation coefficient between module members > 0.80 and intra-module connectivity ≥5. Finally, based on the results of GWSA and hub gene Venn analysis, seven key genes (ACSS2, HECW2, KDR, LHCGR, NAMPT, PTGFR and TFPI) were found to be associated with steroid synthesis and follicle growth development. This work contributes to understanding of the genetic basis of goat litter size and provides theoretical support for goat molecular breeding.

Genetic Foundation of Male Spur Length and Its Correlation with Female Egg Production in Chickens.

Spurs, which mainly appear in roosters, are protrusions near the tarsometatarsus on both sides of the calves of chickens, and are connected to the tarsometatarsus by a bony core. As a male-biased morphological characteristic, the diameter and length of spurs vary significantly between different individuals, mainly related to genetics and age. As a specific behavior of hens, egg-laying also varies greatly between individuals in terms of traits such as age at first egg (AFE), egg weight (EW), and so on. At present, there are few studies on chicken spurs. In this study, we investigated the inheritance pattern of the spur trait in roosters with different phenotypes and the correlations between spur length, body weight at 18 weeks of age (BW18), shank length at 18 weeks of age (SL18), and the egg-laying trait in hens (both hens and roosters were from the same population and were grouped according to their family). These traits related to egg production included AFE, body weight at first egg (BWA), and first egg weight (FEW). We estimated genetic parameters based on pedigree and phenotype data, and used variance analysis to calculate broad-sense heritability for correcting the parameter estimation results. The results showed that the heritability of male left and right spurs ranged from 0.6 to 0.7. There were significant positive correlations between left and right spur length, BW18, SL18, and BWA, as well as between left and right spur length and AFE. We selected 35 males with the longest spurs and 35 males with the shortest spurs in the population, and pooled them into two sets to obtain the pooled genome sequencing data. After genome-wide association and genome divergency analysis by FST, allele frequency differences (AFDs), and XPEHH methods, we identified 7 overlapping genes (CENPE, FAT1, FAM149A, MANBA, NFKB1, SORBS2, UBE2D3) and 14 peak genes (SAMD12, TSPAN5, ENSGALG00000050071, ENSGALG00000053133, ENSGALG00000050348, CNTN5, TRPC6, ENSGALG00000047655,TMSB4X, LIX1, CKB, NEBL, PRTFDC1, MLLT10) related to left and right spur length through genome-wide selection signature analysis and a genome-wide association approach. Our results identified candidate genes associated with chicken spurs, which helps to understand the genetic mechanism of this trait and carry out subsequent research around it.

Evidence for gene flow and trait reversal during radiation of Mexican Goodeid fish

Understanding the phylogeographic history of a group and identifying the factors contributing to speciation is an important challenge in evolutionary biology. The Goodeinae are a group of live-bearing fishes endemic to Mexico. Here, we develop genomic resources for species within the Goodeinae and use phylogenomic approaches to characterise their evolutionary history. We sequenced, assembled and annotated the genomes of four Goodeinae species, including Ataeniobius toweri, the only matrotrophic live-bearing fish without a trophotaenia in the group. We estimated timings of species divergence and examined the extent and timing of introgression between the species to assess if this may have occurred during an early radiation, or in more recent episodes of secondary contact. We used branch-site models to detect genome-wide positive selection across Goodeinae, and we specifically asked whether this differs in A. toweri, where loss of placental viviparity has recently occurred. We found evidence of gene flow between geographically isolated species, suggesting vicariant speciation was supplemented by limited post-speciation gene flow, and gene flow may explain previous uncertainties about Goodeid phylogeny. Genes under positive selection in the group are likely to be associated with the switch to live-bearing. Overall, our studies suggest that both volcanism-driven vicariance and changes in reproductive mode influenced radiation in the Goodeinae.

Genome-wide comparative analysis reveals selection signatures for reproduction traits in prolific Suffolk sheep.

The identification of genome-wide selection signatures can reveal the potential genetic mechanisms involved in the generation of new breeds through natural or artificial selection. In this study, we screened the genome-wide selection signatures of prolific Suffolk sheep, a new strain of multiparous mutton sheep, to identify candidate genes for reproduction traits and unravel the germplasm characteristics and population genetic evolution of this new strain of Suffolk sheep. Whole-genome resequencing was performed at an effective sequencing depth of 20× for genomic diversity and population structure analysis. Additionally, selection signatures were investigated in prolific Suffolk sheep, Suffolk sheep, and Hu sheep using fixation index (F ST) and heterozygosity H) analysis. A total of 5,236.338Gb of high-quality genomic data and 28,767,952 SNPs were obtained for prolific Suffolk sheep. Moreover, 99 selection signals spanning candidate genes were identified. Twenty-three genes were significantly associated with KEGG pathway and Gene Ontology terms related to reproduction, growth, immunity, and metabolism. Through selective signal analysis, genes such as ARHGEF4, CATIP, and CCDC115 were found to be significantly correlated with reproductive traits in prolific Suffolk sheep and were highly associated with the mTOR signaling pathway, the melanogenic pathway, and the Hippo signaling pathways, among others. These results contribute to the understanding of the evolution of artificial selection in prolific Suffolk sheep and provide candidate reproduction-related genes that may be beneficial for the establishment of new sheep breeds.

Differentiating mechanism from outcome for ancestry-assortative mating in admixed human populations.

Population genetic theory, and the empirical methods built upon it, often assume that individuals pair randomly for reproduction. However, natural populations frequently violate this assumption, which may potentially confound genome-wide association studies, selection scans, and demographic inference. Within several recently admixed human populations, empirical genetic studies have reported a correlation in global ancestry proportion between spouses, referred to as ancestry-assortative mating. Here, we use forward genomic simulations to link correlations in ancestry between mates to the underlying mechanistic mate-choice process. We consider the impacts of two types of mate-choice model, using either ancestry-based preferences or social groups as the basis for mate pairing. We find that multiple mate-choice models can produce the same correlations in ancestry proportion between spouses; however, we also highlight alternative analytic approaches and circumstances in which these models may be distinguished. With this work, we seek to highlight potential pitfalls when interpreting correlations in empirical data as evidence for a particular model of human mating practices, as well as to offer suggestions toward development of new best practices for analysis of human ancestry-assortative mating.

Whole-genome resequencing reveals genomic variation and dynamics in Ethiopian indigenous goats

Ethiopia has about 52 million indigenous goats with marked phenotypic variability, which is the outcome of natural and artificial selection. Here, we obtained whole-genome sequence data of three Ethiopian indigenous goat populations (Arab, Fellata, and Oromo) from northwestern Ethiopia and analyzed their genome-wide genetic diversity, population structure, and signatures of selection. We included genotype data from four other Ethiopian goat populations (Abergelle, Keffa, Gumuz, and Woyto-Guji) and goats from Asia; Europe; and eastern, southern, western, and northern Africa to investigate the genetic predisposition of the three Ethiopian populations and performed comparative genomic analysis. Genetic diversity analysis showed that Fellata goats exhibited the lowest heterozygosity values (Ho = 0.288 ± 0.005 and He = 0.334 ± 0.0001). The highest values were observed in Arab goats (Ho = 0.310 ± 0.010 and He = 0.347 ± 4.35e−05). A higher inbreeding coefficient (FROH = 0.137 ± 0.016) was recorded for Fellata goats than the 0.105 ± 0.030 recorded for Arab and the 0.112 ± 0.034 recorded for Oromo goats. This indicates that the Fellata goat population should be prioritized in future conservation activities. The three goat populations showed the majority (∼63%) of runs of homozygosity in the shorter (100–150 Kb) length category, illustrating ancient inbreeding and/or small founder effects. Population relationship and structure analysis separated the Ethiopian indigenous goats into two distinct genetic clusters lacking phylogeographic structure. Arab, Fellata, Oromo, Abergelle, and Keffa represented one genetic cluster. Gumuz and Woyto-Guji formed a separate cluster and shared a common genetic background with the Kenyan Boran goat. Genome-wide selection signature analysis identified nine strongest regions spanning 163 genes influencing adaptation to arid and semi-arid environments (HOXC12, HOXC13, HOXC4, HOXC6, and HOXC9, MAPK8IP2), immune response (IL18, TYK2, ICAM3, ADGRG1, and ADGRG3), and production and reproduction (RARG and DNMT1). Our results provide insights into a thorough understanding of genetic architecture underlying selection signatures in Ethiopian indigenous goats in a semi-arid tropical environment and deliver valuable information for goat genetic improvement, conservation strategy, genome-wide association study, and marker-assisted breeding.

Insights into the genetic architecture of Phytophthora capsici root rot resistance in chile pepper (Capsicum spp.) from multi-locus genome-wide association study

BackgroundPhytophthora root rot, a major constraint in chile pepper production worldwide, is caused by the soil-borne oomycete, Phytophthora capsici. This study aimed to detect significant regions in the Capsicum genome linked to Phytophthora root rot resistance using a panel consisting of 157 Capsicum spp. genotypes. Multi-locus genome wide association study (GWAS) was conducted using single nucleotide polymorphism (SNP) markers derived from genotyping-by-sequencing (GBS). Individual plants were separately inoculated with P. capsici isolates, ‘PWB-185’, ‘PWB-186’, and ‘6347’, at the 4–8 leaf stage and were scored for disease symptoms up to 14-days post-inoculation. Disease scores were used to calculate disease parameters including disease severity index percentage, percent of resistant plants, area under disease progress curve, and estimated marginal means for each genotype.ResultsMost of the genotypes displayed root rot symptoms, whereas five accessions were completely resistant to all the isolates and displayed no symptoms of infection. A total of 55,117 SNP markers derived from GBS were used to perform multi-locus GWAS which identified 330 significant SNP markers associated with disease resistance. Of these, 56 SNP markers distributed across all the 12 chromosomes were common across the isolates, indicating association with more durable resistance. Candidate genes including nucleotide-binding site leucine-rich repeat (NBS-LRR), systemic acquired resistance (SAR8.2), and receptor-like kinase (RLKs), were identified within 0.5 Mb of the associated markers.ConclusionsResults will be used to improve resistance to Phytophthora root rot in chile pepper by the development of Kompetitive allele-specific markers (KASP®) for marker validation, genomewide selection, and marker-assisted breeding.

Whole genome resequencing reveals genomic regions related to red plumage in ducks

Plumage color is a characteristic trait of ducks that originates as a result of natural and artificial selection. As a conspicuous phenotypic feature, it is a breed characteristic. Previous studies have identified some genes associated with the formation of black and white plumage in ducks. However, studies on the genetic basis underlying the red plumage phenotype in ducks are limited. Here, genome-wide association analysis (GWAS) and selection signal detection (Fst, θπ ratio, and cross-population composite likelihood ratio [XP-CLR]) were conducted to identify candidate regions and genes underlying duck plumage color phenotype. Selection signal detection revealed 29 overlapping genes (including ENPP1 and ULK1) significantly associated with red plumage color in Ji'an Red ducks. ENSAPLG00000012679, ESRRG, and SPATA5 were identified as candidate genes associated with red plumage using GWAS. Selection signal detection revealed that 19 overlapping genes (including GMDS, PDIA6, and ODC1) significantly correlated with light brown plumage in Brown Tsaiya ducks. GWAS to narrow down the significant regions further revealed nine candidate genes (AKT1, ATP6V1C2, GMDS, LRP4, MAML3, PDIA6, PLD5, TMEM63B, and TSPAN8). Notably, in Brown Tsaiya ducks, GMDS, ODC1, and PDIA6 exhibit significantly differentiated allele frequencies among other feather-colored ducks, while in Ji'an Red ducks, ENSAPLG00000012679 has different allele frequency distributions compared with that in other feather-colored ducks. This study offers new insights into the variation and selection of the red plumage phenotype using GWAS and selective signals.