羊重要性状全基因组关联分析研究进展

全基因组关联分析(genome-wide association study, GWAS)是一种复杂性状功能基因鉴定的分析策略,已成为挖掘畜禽重要经济性状候选基因的重要手段。随着绵羊和山羊基因组完成和公布,以及不同密度的SNP (single nucleotide polymorphism)芯片的推出并进行商业化推广,不仅大大丰富了羊标记辅助选择可利用的分子标记,而且还为开展重要性状的分子机理的探索提供了重要技术支撑。本文主要针对羊角、羊毛、羊奶、生长发育、肉质、繁殖和疾病等重要性状的GWAS研究所用的群体、主要研究方法和研究结果进行了综述,并对GWAS方法研究现状进行了归纳,以期为进一步利用GWAS进行羊的各种性状的遗传基础研究提供参考。     

马属动物全基因组高通量测序研究进展

马属(Equus)动物的祖先大约在5500万年前出现,经过持续分化形成现今的马、驴和斑马,统称马属动物。马作为家畜中的重要一员,是推动人类文明发展的载体,在人类的饮食、战争、农耕、运输和娱乐等领域做出了巨大贡献。然而,人类为了满足需求,或多或少影响着马的进化方向,从而在长时间自然和人工选择过程中形成了多种独具特色性状的不同马种。驴和骡在全球的存栏量也较多,在人类的生产和生活中起到的作用同样不可忽视,不但为人类提供了生产力而且还提供了食物和营养保健品。可见,马属动物对人类的重要性。近年来,高通量测序技术和生物信息学分析方法被广泛运用于家畜的遗传学研究。人们利用高通量测序手段探索马属动物在进化过程中的种群变化历史,解析形成独特性状的分子机制,为其育种工作提供有效的数据支持。本文综述了马属动物全基因组高通量测序的研究进展,以及利用该技术在马属动物的进化历史和功能基因挖掘研究领域所取得的成就,以期今后对马属动物的深入研究、产业开发和利用等方面提供参考信息。     

高通量测序检测金针菇RNAi转化子插入位点及拷贝数

本研究对金针菇Flammulina velutipes的一个RNAi转化子菌株1382R3进行了高通量测序,以本实验室先前获得的野生型W23基因组数据为参考,分析了该转化子的基因插入位点以及拷贝数。转化子菌株1382R3是通过农杆菌介导将fv-hmg1-RNAi载体转化至金针菇菌株并通过PCR检测筛选标记而得到。通过BLAST将转化子测序的reads对外源载体和基因组定位,找到具有基因组序列（GS）和外源载体序列（ES）两种序列的临界reads,并据此使用PERL语言程序成功在转化子1382R3菌株中找到两个插入位点。对两个插入位置的序列分析表明：在插入位点1,T-DNA片段部分插入;在插入位点2,T-DNA全部插入到基因组。两个插入位点都对基因组内源基因的表达造成了一定的干扰。此方法拓宽了高通量测序技术的应用范围,将其运用到遗传转化插入位置和拷贝数的研究中,有利于食用菌的功能基因组及基因工程研究。     

Functional mapping of N deficiency‐induced response in wheat yield‐component traits by implementing high‐throughput phenotyping

As overfertilization leads to environmental concerns and the cost of N fertilizer increases, the issue of how to select crop cultivars that can produce high yields on N‐deficient soils has become crucially important. However, little information is known about the genetic mechanisms by which crops respond to environmental changes induced by N signaling. Here, we dissected the genetic architecture of N‐induced phenotypic plasticity in bread wheat (Triticum aestivum L.) by integrating functional mapping and semiautomatic high‐throughput phenotyping data of yield‐related canopy architecture. We identified a set of quantitative trait loci (QTLs) that determined the pattern and magnitude of how wheat cultivars responded to low N stress from normal N supply throughout the wheat life cycle. This analysis highlighted the phenological landscape of genetic effects exerted by individual QTLs, as well as their interactions with N‐induced signals and with canopy measurement angles. This information may shed light on our mechanistic understanding of plant adaptation and provide valuable information for the breeding of N‐deficiency tolerant wheat varieties.     

High-throughput characterization,correlation, and mapping of leaf photosynthetic and functional traits in the soybean (Glycine max) nested association mapping population

Photosynthesis is a key target to improve crop production in many species including soybean [Glycine max (L.) Merr.]. A challenge is that phenotyping photosynthetic traits by traditional approaches is slow and destructive. There is proof-of-concept for leaf hyperspectral reflectance as a rapid method to model photosynthetic traits. However, the crucial step of demonstrating that hyperspectral approaches can be used to advance understanding of the genetic architecture of photosynthetic traits is untested. To address this challenge, we used full-range (500–2,400 nm) leaf reflectance spectroscopy to build partial least squares regression models to estimate leaf traits, including the rate-limiting processes of photosynthesis, maximum Rubisco carboxylation rate, and maximum electron transport. In total, 11 models were produced from a diverse population of soybean sampled over multiple field seasons to estimate photosynthetic parameters, chlorophyll content, leaf carbon and leaf nitrogen percentage, and specific leaf area (with R² from 0.56 to 0.96 and root mean square error approximately <10% of the range of calibration data). We explore the utility of these models by applying them to the soybean nested association mapping population, which showed variability in photosynthetic and leaf traits. Genetic mapping provided insights into the underlying genetic architecture of photosynthetic traits and potential improvement in soybean. Notably, the maximum Rubisco carboxylation rate mapped to a region of chromosome 19 containing genes encoding multiple small subunits of Rubisco. We also mapped the maximum electron transport rate to a region of chromosome 10 containing a fructose 1,6-bisphosphatase gene, encoding an important enzyme in the regeneration of ribulose 1,5-bisphosphate and the sucrose biosynthetic pathway. The estimated rate-limiting steps of photosynthesis were low or negatively correlated with yield suggesting that these traits are not influenced by the same genetic mechanisms and are not limiting yield in the soybean NAM population. Leaf carbon percentage, leaf nitrogen percentage, and specific leaf area showed strong correlations with yield and may be of interest in breeding programs as a proxy for yield. This work is among the first to use hyperspectral reflectance to model and map the genetic architecture of the rate-limiting steps of photosynthesis.     

Identification of genetic loci associated with growth traits at weaning in yak through a genome-wide association study

A multilocus GWAS was performed to explore the genetic architecture of four growth traits in yak. In total, 354 female yaks for which measurements of body weight (BW), withers height (WH), body length (BL) and chest girth (CG) at weaning were available underwent genotyping with the Illumina BovineHD BeadChip (770K). After quality control, we retained 98 688 SNPs and 354 animals for GWAS analysis. We identified seven, 18, seven and nine SNPs (corresponding to seven, 17, seven and eight candidate genes) associated with BW, WH, BL and CG at weaning respectively. Interestingly, most of these candidate genes were reported to be involved in growth-related processes such as muscle formation, lipid deposition, feed efficiency, carcass composition and development of the central and peripheral nervous system. Our results offer novel insight into the molecular architecture underpinning yak growth traits. Further functional analyses are thus warranted to explore the molecular mechanisms whereby these genes affect these traits of interest.     

Single step genome-wide association studies based on genotyping by sequence data reveals novel loci for the litter traits of domestic pigs

In this study, data genotyping by sequence (GBS) was used to perform single step GWAS (ssGWAS) to identify SNPs associated with the litter traits in domestic pigs and search for candidate genes in the region of significant SNPs. After quality control, 167,355 high-quality SNPs from 532 pigs were obtained. Phenotypic traits on 2112 gilt litters from 532 pigs were recorded including total number born (TNB), number born alive (NBA), and litter weight born alive (LWB). A single-step genomic BLUP approach (ssGBLUP) was used to implement the genome-wide association analysis at a 5% genome-wide significance level. A total of 8, 23 and 20 significant SNPs were associated with TNB, NBA, and LWB, respectively, and these significant SNPs accounted for 62.78%, 79.75%, and 58.79% of genetic variance. Furthermore, 1 (SSC14: 16314857), 4 (SSC1: 81986236, SSC1: 66599775, SSC1: 161999013, and SSC1: 267883107), and 5 (SSC9: 29030061, SSC2: 32368561, SSC5: 110375350, SSC13: 45619882 and SSC13: 45647829) significant SNPs for TNB, NBA, and LWB were inferred to be novel loci. At SSC1, the AIM1 and FOXO3 genes were found to be associated with NBA; these genes increase ovarian reproductive capacity and follicle number and decrease gonadotropin levels. The genes SLC36A4 and INTU are involved in cell growth, cytogenesis and development were found to be associated with LWB. These significant SNPs can be used as an indication for regions in the Sus scrofa genome for variability in litter traits, but further studies are expected to confirm causative mutations.     

A genome‐wide association study of 23 agronomic traits in Chinese wheat landraces

Uncovering the genetic basis of agronomic traits in wheat landraces is important for ensuring global food security via the development of improved varieties. Here, 723 wheat landraces from 10 Chinese agro‐ecological zones were evaluated for 23 agronomic traits in six environments. All accessions could be clustered into five subgroups based on phenotypic data via discriminant function analysis, which was highly consistent with genotypic classification. A genome‐wide association study was conducted for these traits using 52 303 DArT‐seq markers to identify marker‐trait associations and candidate genes. Using both the general linear model and the mixed linear model, 149 significant markers were identified for 21 agronomic traits based on best linear unbiased prediction values. Considering the linkage disequilibrium decay distance in this study, significant markers within 10 cM were combined as a quantitative trait locus (QTL), with a total of 29 QTL identified for 15 traits. Of these, five QTL for heading date, flag leaf width, peduncle length, and thousand kernel weight had been reported previously. Twenty‐five candidate genes associated with significant markers were identified. These included the known vernalization genes VRN‐B1 and vrn‐B3 and the photoperiod response genes Ppd and PRR. Overall, this study should be helpful in elucidating the underlying genetic mechanisms of complex agronomic traits and performing marker‐assisted selection in wheat.     

Genetic dissection of drought and heat‐responsive agronomic traits in wheat

High yield and wide adaptation are principal targets of wheat breeding but are hindered by limited knowledge on genetic basis of agronomic traits and abiotic stress tolerances. In this study, 277 wheat accessions were phenotyped across 30 environments with non‐stress, drought‐stressed, heat‐stressed, and drought‐heat‐stressed treatments and were subjected to genome‐wide association study using 395 681 single nucleotide polymorphisms. We detected 295 associated loci including consistent loci for agronomic traits across different treatments and eurytopic loci for multiple abiotic stress tolerances. A total of 22 loci overlapped with quantitative trait loci identified by biparental quantitative trait loci mapping. Six loci were simultaneously associated with agronomic traits and abiotic stress tolerance, four of which fell within selective sweep regions. Selection in Chinese wheat has increased the frequency of superior marker alleles controlling yield‐related traits in the four loci during past decades, which conversely diminished favourable genetic variation controlling abiotic stress tolerance in the same loci; two promising candidate paralogous genes colocalized with such loci, thereby providing potential targets for studying the molecular mechanism of stress tolerance–productivity trade‐off. These results uncovering promising alleles controlling agronomic traits and/or multiple abiotic stress tolerances, providing insights into heritable covariation between yield and abiotic stress tolerance, will accelerate future efforts for wheat improvement.     

Population structure and genetic basis of the agronomic traits of upland cotton in China revealed by a genome‐wide association study using high‐density SNPs

Gossypium hirsutum L. represents the largest source of textile fibre, and China is one of the largest cotton‐producing and cotton‐consuming countries in the world. To investigate the genetic architecture of the agronomic traits of upland cotton in China, a diverse and nationwide population containing 503 G. hirsutum accessions was collected for a genome‐wide association study (GWAS) on 16 agronomic traits. The accessions were planted in four places from 2012 to 2013 for phenotyping. The CottonSNP63K array and a published high‐density map based on this array were used for genotyping. The 503 G. hirsutum accessions were divided into three subpopulations based on 11 975 quantified polymorphic single‐nucleotide polymorphisms (SNPs). By comparing the genetic structure and phenotypic variation among three genetic subpopulations, seven geographic distributions and four breeding periods, we found that geographic distribution and breeding period were not the determinants of genetic structure. In addition, no obvious phenotypic differentiations were found among the three subpopulations, even though they had different genetic backgrounds. A total of 324 SNPs and 160 candidate quantitative trait loci (QTL) regions were identified as significantly associated with the 16 agronomic traits. A network was established for multieffects in QTLs and interassociations among traits. Thirty‐eight associated regions had pleiotropic effects controlling more than one trait. One candidate gene, Gh_D08G2376, was speculated to control the lint percentage (LP). This GWAS is the first report using high‐resolution SNPs in upland cotton in China to comprehensively investigate agronomic traits, and it provides a fundamental resource for cotton genetic research and breeding.     

Comprehensive genomic analyses of Vigna unguiculata provide insights into population differentiation and the genetic basis of key agricultural traits

Vigna unguiculata is an important legume crop worldwide. The subsp. sesquipedalis and unguiculata are the two major types grown; the former is mainly grown in Asia to produce fresh pods, while the latter is mainly grown in Africa to produce seeds. Here, a chromosome-scale genome for subsp. sesquipedalis was generated by combining high-fidelity (HiFi) long-read sequencing with high-throughput chromosome conformation capture (Hi-C) technology. The genome size for all contigs and N50 were 594 and 18.5 Mb, respectively. The Hi-C interaction map helped cluster 91% of the contigs into 11 chromosomes. Genome comparisons between subsp. sesquipedalis and unguiculata revealed extensive genomic variations, and some variations resulted in gene loss. A germplasm panel with 315 accessions of V. unguiculata was resequenced, and a genomic variation map was constructed. Population structure and phylogenetic analyses suggested that subsp. sesquipedalis originated from subsp. unguiculata. Highly differentiated genomic regions were also identified, and a number of genes functionally enriched in adaptations were located in these regions. Two traits, pod length (PL) and pod width (PW), were observed for this germplasm, and genome-wide association analysis of these traits was performed. The quantitative trait loci (QTLs) for these two traits were identified, and their candidate genes were uncovered. Interestingly, genomic regions of PL QTLs also showed strong signals of artificial selection. Taken together, the results of this study provide novel insights into the population differentiation and genetic basis of key agricultural traits in V. unguiculata.     

Elucidating the genetic basis of biomass accumulation and radiation use efficiency in spring wheat and its role in yield potential

One of the major challenges for plant scientists is increasing wheat (Triticum aestivum) yield potential (YP). A significant bottleneck for increasing YP is achieving increased biomass through optimization of radiation use efficiency (RUE) along the crop cycle. Exotic material such as landraces and synthetic wheat has been incorporated into breeding programmes in an attempt to alleviate this; however, their contribution to YP is still unclear. To understand the genetic basis of biomass accumulation and RUE, we applied genome‐wide association study (GWAS) to a panel of 150 elite spring wheat genotypes including many landrace and synthetically derived lines. The panel was evaluated for 31 traits over 2 years under optimal growing conditions and genotyped using the 35K wheat breeders array. Marker‐trait association identified 94 SNPs significantly associated with yield, agronomic and phenology‐related traits along with RUE and final biomass (BM_PM) at various growth stages that explained 7%–17% of phenotypic variation. Common SNP markers were identified for grain yield, BM_PM and RUE on chromosomes 5A and 7A. Additionally, landrace and synthetic derivative lines showed higher thousand grain weight (TGW), BM_PM and RUE but lower grain number (GM2) and harvest index (HI). Our work demonstrates the use of exotic material as a valuable resource to increase YP. It also provides markers for use in marker‐assisted breeding to systematically increase BM_PM, RUE and TGW and avoid the TGW/GM2 and BM_PM/HI trade‐off. Thus, achieving greater genetic gains in elite germplasm while also highlighting genomic regions and candidate genes for further study.     

Generality and characteristics of genetic and epigenetic changes in newly synthesized allotetraploid wheat lines

Previous studies have shown rapid and extensive genomic instability associated with early stages of allopolyploidization in wheat.However, these studies are based on either a few pre-selected genomic loci or genome-wide analysis of a single plant individual for a given cross combination, thus making the extent and generality of the changes uncertain.To further study the generality and characteristics of allopolyploidization-induced genomic instability in wheat, we investigated genetic and epigenetic changes from a genome-wide perspective (by using the AFLP and MSAP markers) in four sets of newly synthesized allotetraploid wheat lines with various genome constitutions, each containing three randomly chosen individual plants at the same generation.We document that although general chromosomal stability was characteristic of all four sets of allotetraploid wheat lines, genetic and epigenetic changes at the molecular level occurred in all these plants, with both kinds of changes classifiable into two distinct categories, i.e., stochastic and directed.The abundant type of genetic change is loss of parental bands while the prevalent cytosine methylation pattern alteration is hypermethylation at the CHG sites.Our results have extended previous studies regarding allopolyploidization-induced genomic dynamics in wheat by demonstrating the generality of both genetic and epigenetic changes associated with multiple nascent allotetraploid wheat lines, and providing novel insights into the characteristics of the two kinds of induced genomic instabilities.     

High‐throughput two‐dimensional root system phenotyping platform facilitates genetic analysis of root growth and development

High‐throughput phenotyping of root systems requires a combination of specialized techniques and adaptable plant growth, root imaging and software tools. A custom phenotyping platform was designed to capture images of whole root systems, and novel software tools were developed to process and analyse these images. The platform and its components are adaptable to a wide range root phenotyping studies using diverse growth systems (hydroponics, paper pouches, gel and soil) involving several plant species, including, but not limited to, rice, maize, sorghum, tomato and Arabidopsis. The RootReader2D software tool is free and publicly available and was designed with both user‐guided and automated features that increase flexibility and enhance efficiency when measuring root growth traits from specific roots or entire root systems during large‐scale phenotyping studies. To demonstrate the unique capabilities and high‐throughput capacity of this phenotyping platform for studying root systems, genome‐wide association studies on rice (Oryza sativa) and maize (Zea mays) root growth were performed and root traits related to aluminium (Al) tolerance were analysed on the parents of the maize nested association mapping (NAM) population.     

我国旱地春小麦产量及主要农艺指标的变异分析

采用4年、13个品种(系)、18个试点组成的全国旱地春小麦区域试验产量资料,通过联合方差分析和基因型及其与环境互作（GGE）双标图分析,研究了基因型、环境、基因型与环境互作效应（GEI）对产量变异的影响及品种的产量稳定性.结果表明：环境对产量变异的影响远大于基因型和GEI,环境引起的产量变异占87.5%～92.0%．互作因素中以地点×基因型的互作效应最大,基因型×年份的互作效应最小.我国旱地春小麦基因型多年多点的平均产量水平为2550 kg·hm^-2.产量三要素中,千粒重受环境的影响最小.影响产量变异的主要环境因子有：≥10 ℃年积温、生育期降雨量、平均气温、海拔、年降雨量和无霜期.产量与单位面积穗数（0.675^**）、穗粒数（0.581^**）、千粒重（0.456^**）呈极显著正相关,产量三要素间也呈正相关（0.244～0.480^**）,处于可同步提高范围.     

Resequencing and signatures of selection scan in two Siberian native sheep breeds point to candidate genetic variants for adaptation and economically important traits

Russian sheep breeds represent an important economic asset by providing meat and wool, whilst being adapted to extreme climates. By resequencing two Russian breeds from Siberia: Tuva (n = 20) and Baikal (n = 20); and comparing them with a European (UK) sheep outgroup (n = 14), 41 million variants were called, and signatures of selection were identified. High‐frequency missense mutations on top of selection peaks were found in genes related to immunity (LOC101109746) in the Baikal breed and wool traits (IDUA), cell differentiation (GLIS1) and fat deposition (AADACL3) in the Tuva breed. In addition, genes found under selection owing to haplotype frequency changes were related to wool traits (DSC2), parasite resistance (CLCA1), insulin receptor pathway (SOCS6) and DNA repair (DDB2) in the Baikal breed, and vision (GPR179) in the Tuva breed. Our results present candidate genes and SNPs for future selection programmes, which are necessary to maintain and increase socioeconomic gain from Siberian breeds.     

Analysis of the genetic architecture of maize kernel size traits by combined linkage and association mapping

Kernel size‐related traits are the most direct traits correlating with grain yield. The genetic basis of three kernel traits of maize, kernel length (KL), kernel width (KW) and kernel thickness (KT), was investigated in an association panel and a biparental population. A total of 21 single nucleotide polymorphisms (SNPs) were detected to be most significantly (P < 2.25 × 10^?6) associated with these three traits in the association panel under four environments. Furthermore, 50 quantitative trait loci (QTL) controlling these traits were detected in seven environments in the intermated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population, of which eight were repetitively identified in at least three environments. Combining the two mapping populations revealed that 56 SNPs (P < 1 × 10^?3) fell within 18 of the QTL confidence intervals. According to the top significant SNPs, stable‐effect SNPs and the co‐localized SNPs by association analysis and linkage mapping, a total of 73 candidate genes were identified, regulating seed development. Additionally, seven miRNAs were found to situate within the linkage disequilibrium (LD) regions of the co‐localized SNPs, of which zma‐miR164e was demonstrated to cleave the mRNAs of Arabidopsis CUC1, CUC2 and NAC6 in vitro. Overexpression of zma‐miR164e resulted in the down‐regulation of these genes above and the failure of seed formation in Arabidopsis pods, with the increased branch number. These findings provide insights into the mechanism of seed development and the improvement of molecular marker‐assisted selection (MAS) for high‐yield breeding in maize.     

New insights into the genetic basis of natural chilling and cold shock tolerance in rice by genome‐wide association analysis

In order to understand cold adaptability and explore additional genetic resources for the cold tolerance improvement of rice, we investigated the genetic variation of 529 rice accessions under natural chilling and cold shock stress conditions at the seedling stage using genome‐wide association studies; a total of 132 loci were identified. Among them, 12 loci were common for both chilling and cold shock tolerance, suggesting that rice has a distinct and overlapping genetic response and adaptation to the two stresses. Haplotype analysis of a known gene OsMYB2, which is involved in cold tolerance, revealed indica–japonica differentiation and latitude tendency for the haplotypes of this gene. By checking the subpopulation and geographical distribution of accessions with tolerance or sensitivity under these two stress conditions, we found that the chilling tolerance group, which mainly consisted of japonica accessions, has a wider latitudinal distribution than the chilling sensitivity group. We conclude that the genetic basis of natural chilling stress tolerance in rice is distinct from that of cold shock stress frequently used for low‐temperature treatment in the laboratory and the cold adaptability of rice is associated with the subpopulation and latitudinal distribution.