Epistatic partners of neurogenic genes modulate Drosophila olfactory behavior

The extent to which epistasis affects the genetic architecture of complex traits is difficult to quantify, and identifying variants in natural populations with epistatic interactions is challenging. Previous studies in Drosophila implicated extensive epistasis between variants in genes that affect neural connectivity and contribute to natural variation in olfactory response to benzaldehyde. In this study, we implemented a powerful screen to quantify the extent of epistasis as well as identify candidate interacting variants using 203 inbred wild‐derived lines with sequenced genomes of the Drosophila melanogaster Genetic Reference Panel (DGRP). We crossed the DGRP lines to P[GT1]‐element insertion mutants in Sema‐5c and neuralized (neur), two neurodevelopmental loci which affect olfactory behavior, and to their coisogenic wild‐type control. We observed significant variation in olfactory responses to benzaldehyde among F₁ genotypes and for the DGRP line by mutant genotype interactions for both loci, showing extensive nonadditive genetic variation. We performed genome‐wide association analyses to identify the candidate modifier loci. None of these polymorphisms were in or near the focal genes; therefore, epistasis is the cause of the nonadditive genetic variance. Candidate genes could be placed in interaction networks. Several candidate modifiers are associated with neural development. Analyses of mutants of candidate epistatic partners with neur (merry‐go‐round (mgr), prospero (pros), CG10098, Alhambra (Alh) and CG12535) and Sema‐5c (CG42540 and bruchpilot (brp)) showed aberrant olfactory responses compared with coisogenic controls. Thus, integrating genome‐wide analyses of natural variants with mutations at defined genomic locations in a common coisogenic background can unmask specific epistatic modifiers of behavioral phenotypes.     

棉花花铃期抗旱性综合评价及指标筛选

以90份国内棉花为材料,在大田采用花铃期胁迫,考察6个农艺性状和单株产量(Y值)指标,采用综合抗旱系数、因子分析、隶属性函数值、聚类分析、灰色关联度和广义遗传力分析相结合的方法,对其抗旱性进行综合评价、抗旱性划分和评价指标筛选。结果表明,基于D值相关性状指标对干旱胁迫关联度位次依次为:单株产量、有效铃数、有效果枝数、株高、单铃重、衣分、第一果枝节位。因子分析表明,3个公因子可代表棉花抗旱性72.45%的原始数据信息量。基于D值和加权抗旱系数(WDC值)的各品种抗旱性排序相近,位居前10位的抗旱品种基本相同。各品种D值与综合抗旱系数(CDC值)、WDC值之间均呈极显著正相关,广义遗传率分析表明D值的遗传率为55.4%,为最高,其次为CDC值、WDC值。各品种Y值与CDC、WDC值间极显著正相关;根据D值将试验材料划分为5个抗旱级别,可较好地反映品种的选育条件及适应地区。试验结果说明基于遗传力大小的综合抗旱指标中用D值为主要参数,WDC为辅助评价参数,评价以单株产量为主要考量目标的棉花抗旱性是适宜且必须的;以抗旱性综合评价方法进行棉花抗旱性综合评价、抗旱性划分和评价指标筛选是可行且有效的。     

高寒草甸高原早熟禾个体性状对放牧与围封的响应

植物对放牧的响应是植物在响应过程中为生存和繁殖所形成的适应策略,研究植物表型反应对揭示草原生态系统的放牧响应机制具有重要意义。以青藏高原高寒草甸主要植物高原早熟禾(Poa alpigena)为研究对象,通过放牧和围封试验,研究其个体性状对放牧与围封的响应,旨在为草原生态系统放牧机制提供理论依据。结果表明:1)在长期放牧干扰下,除叶片数和根重外,其他性状株高、分枝数、叶长、叶宽、叶面积、茎粗、茎长、根长、根粗、穗长、总叶质量、单叶质量、茎重、穗重、全株重均出现显著变小的特征(P0.05);而短期围封对于高原早熟禾叶长、叶宽、总叶质量、单叶质量、茎重、穗重、根重等功能性状的恢复效果并不显著(P0.05),表明放牧退化草原植物性状具有保守性;2)通过构建高原早熟禾性状可塑性变化谱,发现穗重、茎重、全株重、分蘖数、茎长、株高等可塑性幅度较大,为放牧响应的敏感指标,叶片数、叶宽、茎粗、根粗的可塑性变化幅度较小,为惰性性状。     

月季F1代群体表型性状变异分析

以月季（Rosa spp.）品种‘云蒸霞蔚’和‘太阳城’正交获得的184株F₁代群体为研究对象,采用方差分析、变异系数、遗传分析、相关性分析对花部形态性状以及叶片形态性状进行测定分析。结果表明：该杂交群体表型变异丰富,变异系数在7.33%~68.08%,其中花瓣数量在群体中的变异程度最高;杂交后代各个性状上均发生分离变异,出现不同于亲本的表现型,且离散程度较高。表型性状的遗传特点与关联分析,为挖掘控制表型性状的优良基因及辅助选择育种提供参考。     

不同树龄水曲柳半同胞家系生长性状变异研究

为筛选优质的水曲柳种质资源,以吉林省三岔子林业局国家水曲柳良种基地的16年生水曲柳子代测定林75个半同胞家系为材料,分别在第4、11和16年对其树高、地径（胸径）和材积进行测定。方差分析结果表明,不同变异来源各指标均达极显著差异水平（P<0.01）;各指标表型变异系数变化范围为22.20%~63.30%,家系遗传力变化范围为0.796~0.981;相关性分析结果表明各指标间均呈极显著正相关;以材积为评价指标,按10%入选率对家系进行评价选择,初步筛选8个优良家系,入选的家系材积平均值比总平均值高0.007 m³,遗传增益为36.03%;该研究选出的优良家系可为良种登记提供基础,也可为种子园的改建提供材料。     

云南松苗木生长与生物量的相关性及通径分析

为了解云南松苗木生长对生物量的影响程度和相对重要性,以采自云南省昆明市宜良县禄丰村林场种子培育的2年生云南松苗木为材料,对苗高、地径、主根长、侧根长、针叶长和侧根数6个生长性状及各组分生物量进行测定,运用相关性分析和逐步回归分析剔除了对生物量影响不大的性状,在此基础上采用通径分析方法研究了云南松苗木生长性状指标与生物量指标间的关系。结果表明：云南松苗木生长性状和生物量之间均呈现极显著的正相关关系。各生长性状对生物量均有直接或间接的正向效应,直接影响云南松苗木生物量的优势因素为地径和苗高,针叶长、侧根长和主根长对生物量的影响也起正向效应。各生长性状对生物量的直接效应均较大,而通过其他性状的间接效应均较小,其中侧根长通过其他性状对生物量产生的间接影响最大。依据相关性分析和通径分析,建立了云南松各组分生物量与生长性状之间的数学模型,可用于云南松苗期生物量的估测。     

Seasonal distribution of increased precipitation in maternal environments influences offspring performance of Potentilla tanacetifolia in a temperate steppe ecosystem

Aims Precipitation is predicted to increase in arid and semiarid regions under climate change, with greater changes in intra- and inter-annual distribution in the future. As a major limiting factor in these regions, changes in precipitation undoubtedly influence plant growth and productivity. However, how the temporal shifts in precipitation will impact plant populations are uncertain.