Molecular genetics of behaviour: research strategies and perspectives for animal production

Genetic factors are undoubtedly involved in inter-individual variability of the behaviours that may be important for livestock production, as shown by pedigree studies, comparison of genetic stocks raised in the same environment, and selection experiments. The knowledge of gene polymorphisms responsible for genetic variability would increase the efficiency of selection, as shown for instance by the identification of the ryanodine receptor gene that harbours the mutations responsible for the porcine stress syndrome, that allows the eradication of the susceptibility allele. One strategy is to screen systematically the genes that are known to be involved in regulation of behaviour (functional candidate genes). This strategy is however very difficult for most behavioural traits, since behaviour is an emerging function from the whole brain/body and the molecular pathways involved in genetic variability are very poorly understood. Another strategy is to investigate linkage between trait variation and genetic markers in a segregating population (usually an intercross or backcross between two strains or breeds contrasting for the trait under study). It allows the detection of genomic regions influencing that trait (quantitative trait loci or QTL), and further investigation aims at the identification of the gene(s) located in each of these regions and the molecular polymorphisms involved in phenotypic variation. Although many QTL have been published for behavioural traits in experimental animals, very few examples are available where strong candidate genes have been identified. Further progress will be very much dependent upon the careful definition of behavioural traits to be studied (including their importance for animal production), on the reliability of their measurement in a large number of animals and on the efficient mastering of environmental factors of variability. The fast increase in the knowledge of genome sequence in several species will undoubtedly facilitate the application to farm animal species of the knowledge obtained in model organisms, as well as the use of model organisms to explore candidate genes detected by QTL studies in farm animals.     

山东栒子全长转录组测序数据组装及功能注释

山东栒子是中国山东省的特有种,现已处于极度濒危状态。目前,山东栒子的分子生物学研究较少,基因数据库资源极度缺乏,急需探究其生物学遗传信息,以加快对山东栒子的保护遗传学工作。本研究以山东栒子叶片、花、成熟果实为实验材料,利用PacBio Sequel测序平台对其转录组进行全长转录组测序。共得到高质量去冗余的转录本53932个,作为最终转录本序列。预测到的CDS区共52490个;对其SSR位点进行分析,对测序得到Unigenes进行单核苷酸至六核苷酸重复的SSR位点搜索,共搜索到26796个SSR位点。对非冗余转录本利用BLAST软件与NR、Swissprot、GO、COG、KOG、KEGG 6个数据库进行比对,一共成功注释了53319个Unigenes,其中与NR数据库进行比对中注释为苹果的的相关基因数量最多,其次是白梨和桃;在GO数据库中有33305条山东栒子Unigenes被注释分类,由生物学过程、细胞成分和分子功能三部分组成;在与COG数据库比对中,共有23910条比对到了同源序列,且一共被分为25类;在与KEGG数据库的一系列比对中,可将Unigenes映射到126条代谢通路中。本研究在高通量全长转录组水平对山东栒子进行了系统研究,这为进一步开展山东栒子的分子标记开发和挖掘优良基因提供了科学依据,从而推动山东栒子的保护与利用。     

Quantitative trait loci for fruit size and flowering time-related traits under domestication and diversifying selection in cucumber (Cucumis sativus)

In cucumber, the genetic basis of traits under domestication and/or diversifying selection is not well understood. Here, we reported QTL mapping for flowering time and fruit size-related traits with segregating populations derived from a cultivated × wild cross. Phenotypic data of flowering time (FT), fruit size (FS), fruit number (FN) and fruit weight per plant (FW) were collected in multiple environments. QTL analysis identified 19 QTL for these traits. We found that the major-effect QTL FT1.1 played an important role in regulating flowering time in cultivated cucumber, whereas the minor-effect QTL FT6.3 contributed to photoperiod sensitive flowering time during domestication. Two novel consensus FS QTL, FS1.4 and FS2.3, seem to be the targets of selection during breeding for the US processing cucumber. All other FS QTL were co-localized with previously detected QTL using populations derived from cultivated cucumbers, suggesting that they were under selection during both initial domestication and subsequent improvement. Results from this study also suggested that the wild cucumber is a useful resource for capturing positive transgressive segregation and novel alleles that could be explored in cucumber breeding.     

镜鲤体重的QTL定位

本研究利用217个微卫星标记和336个SNPs标记对德国镜鲤F2代68个个体基因组DNA进行基因型检测。其中507个标记共组成62个连锁群,覆盖基因组总长度为2805．85cM,标记问平均距离为6-31cM;利用软件MapQTL4．0采用区间作图法对体重性状进行QTL定位分析。研究结果共检测到14个与体重性状有关的QTLs,分布于9个连锁群。其中BIV-5-J有最大的LOD值,为4．46;BIV—I-1的LOD值最小,为2．25。单个QTL平均解释表型变异介于14．10％～45．50％之间,其中贡献率大于20％的主效QTLs有9个。通过BLASTX与斑马鱼蛋白质序列数据库进行序列比对,找到了与斑马鱼酰基辅酶A脱氢酶蛋白、胰淀粉酶仅2蛋白、Apoebprotein和甘油醛-3-磷酸脱氢酶蛋白同源的分子标记。本研究结果对分子标记辅助育种具有重要应用价值。     

基于染色体单片段代换系的水稻粒形QTL定位

水稻的粒形是影响水稻产量和品质的重要因子之一, 是由多基因控制的数量性状。染色体单片段代换系由于减少了个体间遗传背景的干扰, 已经成为鉴定复杂性状QTL的新型遗传材料。本研究以广陆矮4号为受体,日本晴为供体的119个染色体单片段代换系群体为试验材料,通过单因素方差分析和Dunnett’s多重比较,测验单片段代换系与受体亲本之间粒形的差异,鉴定了代换片段上粒形相关的QTL。以P≤0.001为阈值, 共检测到39个粒形相关的QTL。其中,粒长相关的19个,其加性效应值为0.18~1.06 mm,加性效应百分率为2.40%~14.13%;粒宽相关的14个,其加性效应值为0.09~0.31 mm,加性效应百分率为2.71%~9.15%;粒厚相关的6个,其加性效应值为0.05~0.10 mm,加性效应百分率为2.14%~4.46%。这些QTL的鉴定,为进一步精细定位并克隆相应QTL和高产、优质水稻新品种的分子标记辅助选择奠定了基础。     

利用SSR标记区别小麦品种种子混杂和SSR位点不纯的研究

在用SSR标记检测小麦种子纯度时,种子混杂和SSR位点不纯都会造成株间SSR带型的差异,本文提出了SSR位点不纯的概念,并分析了存在这一现象的原因,指出这一现象普遍存在于小麦品种中。为此在检测小麦种子纯度时,需要注意区别种子混杂和SSR位点不纯,以免将SSR位点不纯造成的株间带型差异误认为是种子混杂,其原则是:(1)必须进行多个SSR位点的检测;(2)某单株的多个SSR位点的带型与被检测品种不同,可确认为混杂植株;(3)剔除混杂植株后,某单株的个别SSR位点的带型与被检测品种不同,将被认为是SSR位点不纯所致。     

Glu-B1位点亚基色谱鉴定及7OE对面团强度的影响

准准确鉴定高分子量谷蛋白亚基（HMW-GS）及探讨其对面团特性的影响是小麦品质研究的重要内容。用聚丙烯酰胺凝胶电泳（SDS-PAGE）和反相高效液相色谱（RP-HPLC）对62份品种（系）的HMW-GS组成进行鉴定。结果表明，结合SDS-PAGE和RP-HPLC两种方法可以对Glu-B1位点，尤其是Glu-B1（7+8）进行有效鉴定。选用13份姊妹系为材料，使用RP-HPLC和凝胶色谱（SE-HPLC）方法，研究了Glu-B1al（7^OE+8*）以及贮藏蛋白组分含量对面团强度的影响。结果表明，Glu-B1al（7^OE+8*）可显著提高HWM-GS总量和面团强度，7OE可作为优质亚基用于强筋小麦育种。相关性分析表明，谷蛋白总量、HWM-GS、LMW-GS以及x-HMW含量与最大抗阻力呈1%显著正相关，相关系数分别为0.76、0.76、0.77和0.72。SDS-不溶性谷蛋白大聚体（UPP）占谷蛋白聚合体总量的百分比与揉面仪峰值时间、粉质仪形成时间和稳定时间以及最大抗阻呈1%或0.1%显著正相关，相关系数分别为0.77、0.90、0.89和0.87。醇溶蛋白与谷蛋白含量的比值与揉面仪峰值时间呈1%显著负相关，相关系数为－0.69；与粉质仪稳定时间和最大抗阻呈5%显著负相关，相关系数分别为－0.58和－0.64。HPLC可有效分离和量化HWM-GS，并作为小麦品质育种有效的辅助手段。     

Identification of QTLs associated with salinity tolerance at late growth stage in barley

Salinity is a major abiotic stress to barley (Hordum vulgare L.) growth and yield. In the current study, quantitative trait loci (QTL) for yield and physiological components at the late growth stage under salt stress and non-stress environments were determined in barley using a double haploid population derived from a cross between CM72 (salt-tolerant) and Gairdner (salt-sensitive). A total of 30 QTLs for 10 traits, including tiller numbers (TN), plant height, spikes per line (SPL), spikes per plant (SPP), dry weight per plant, grains per plant, grain yield, shoot Na⁺ (NA) and K⁺ concentraitions (K) in shoot, and Na⁺/K⁺ ratio (NAK), were detected, with 17 and 13 QTLs under non-stress and salt stress, respectively. The phenotypic variation explained by individual QTL ranged from 3.25 to 29.81%. QTL flanked by markers bPb-1278 and bPb-8437 on chromosomes 4H was associated with TN, SPL, and SPP under salt stress. This locus may be useful in the breeding program of marker-assisted selection for improving salt tolerance of barley. However, QTLs associated with NA, K, and NAK differed greatly between non-stress and salt stress environments. It may be suggested that only the QTLs detected under salt stress are really associated with salt tolerance in barley. D. Xue and Y. Huang contributed equally to the article.     

稻米品质性状与产量性状及籼粳分化度的相互关系研究

通过QTL的连锁关系和性状相关性研究表明,供试的籼粳重组自交系群体的籼粳分化程度与籼、粳稻的直链淀粉含量高低无直接关系,籼粳分化度与胶稠度、碱消值、蛋白质和粗脂肪含量之间呈现显著相关和密切连锁关系;直链淀粉含量的高低不是影响稻米食味品质的关键因素,胶稠度和碱消值是影响稻米食味品质的最重要因素;单株产量越高,     

Identification of QTLs related to sugar and organic acid composition in melon using near-isogenic lines

The soluble sugar and organic acid composition of melon (Cucumis melo L.) fruit flesh has become a major focus of plant breeding worldwide in an attempt to improve taste. Thus, sugar and organic acid profiles were characterized using near-isogenic lines (NILs) derived from the Spanish cultivar Piel de Sapo (PS) and the exotic Korean accession Shongwan Charmi (PI 161375). Fruits were cultivated in only one environment. These data were used to map 60 quantitative trait loci (QTLs): 18 for individual sugars, eight for sucrose equivalents, five for the glucose-to-fructose ratio, seven for the total sugar content and 21 for organic acids. Within the QTLs that were associated with the sugar profile, 27 defined the sugar content: eight for fructose, six for glucose, four for sucrose, and nine for sucrose equivalents. Although increased sweetness of selected NILs compared with the parental PS was achieved by an increased glucose or fructose content, only glucose heritability was above 0.5. A total of 21 QTLs (two with positive effects and nineteen with detrimental effects compared with the PS levels) controlled the organic acid profile: l-glutamic, ascorbic and succinic acids (the principal ones) and fumaric, citric, oxalacetic, and isocitric acids. The levels of sugars imparted by the PI 161375 introgression frequently decreased the score grades given to NILs by consumers. Within the 32 QTLs mapped for sensory traits, 27 were associated with lower scores in taste (nine QTLs), sweetness (eight QTLs) or global quality appreciation (nine QTLs); two with increased fruit sourness or sweetness and three with increased fruit bitterness. The QTLs defined herein may assist breeders to understand the overall organoleptic balance (sweetness, sourness, and umami taste) in melon fruit, particularly those located within linkage groups III, V, VI, and VIII to XI.